Performant model code, high quality data, and robust evaluation methods form the foundation of an AI system. Scale’s leading end-to-end solutions for the ML lifecycle based on real-world data will continue to set the bar for the data-centric AI movement. Scale’s Generative AI team focuses on building models to accelerate AI adoption for some of the largest companies in the world.

Your focus will be on developing Models as a Service using a variety of Machine Learning techniques. You will be involved end-to-end from coordinating with operations to create high quality datasets to productionizing models for our customers. If you are excited about shaping the future of the data-centric AI movement, we would love to hear from you!

You will:

• Apply state of the art models, developed both internally and from the community, in production to solve problems for our customers and data labelers.
• Work with product and research teams to identify opportunities for ongoing and upcoming services.
• Explore approaches that integrate human feedback and assisted evaluation into existing product lines.
• Work closely with customers - some of the most sophisticated ML organizations in the world - to quickly prototype and build new deep learning models targeted at multi-modal content understanding problems.

Ideally you’d have:

• At least 3 to 5 years of model training, deployment and maintenance experience in a production environment.
• Strong skills in NLP, LLM and deep learning.
• Solid background in algorithms, data structures, and object-oriented programming.
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field.
• Demonstrated expertise in large vision-language models for diverse real-world applications, e.g. classification, detection, question-answering, etc.
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals.
• Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kuberflow, TensorFlow, etc.
• Strong written and verbal communication skills to operate in a cross functional team environment.

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $176,000 - $240,960. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are computer vision (2D/3D detection, 2D/3D segmentation, object tracking), meta-learning (e.g. semi-supervised learning, active learning), and Natural Language Processing. You’ll be working on a combination of deeply technical ML applications in production and cutting edge research problems. Working at Scale will give you opportunities to work with our wide customer base which includes leading research teams and exposure to a wide range of problems within machine learning.

We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. Our machine learning models form the basis for Scale’s expansion and future product strategy. We currently complete billions of tasks a month, and will continue to grow to support more complex use cases and more advanced ML powered products.

Example Projects:

• Research and develop machine learning solutions to assist humans in the loop.
• Aid in the creation of high quality ground truth data with speed and accuracy.
• Work with public Large Language models to benchmark and make custom versions for internal use cases.
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
• Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
• Work with massive datasets to develop both generic models as well as fine tune models for specific products.

Required to have:

• Currently enrolled in a PhD or MS Program with a focus on Machine Learning, Deep Learning, Computer Vision with a graduation date in Fall 2024 or Spring 2025
• Experience with one or more general purpose programming languages, including: Python, Javascript, or similar
• Ability to speak and write in English fluently

Ideally you’d have:

• Have had a previous internship around Machine Learning, Deep Learning, or Computer Vision
• Experience as a researcher, including internships, full-time, or at a lab
• Publications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to open source projects

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

The goal of the ML team at Scale is to develop machine learning solutions advancing the company mission. Our current focus areas are computer vision (2D/3D detection, 2D/3D segmentation, object tracking), meta-learning (e.g. semi-supervised learning, active learning), and Natural Language Processing. You’ll be working on a combination of deeply technical ML applications in production and cutting edge research problems. Working at Scale will give you opportunities to work with our wide customer base which includes leading research teams and exposure to a wide range of problems within machine learning.

We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. Our machine learning models form the basis for Scale’s expansion and future product strategy. We currently complete billions of tasks a month, and will continue to grow to support more complex use cases and more advanced ML powered products.

Example Projects:

• Research and develop machine learning solutions to assist humans in the loop.
• Develop systems that improve the creation of high quality ground truth data with speed and accuracy.
• Work with public Large Language models to benchmark and make custom versions for internal use cases.
• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.
• Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics.
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
• Work with massive datasets to develop both generic models as well as fine tune models for specific products.

Required to have:

• Graduating Fall of 2023 or Spring of 2024 from a PhD or MS Program with a focus on Machine Learning, Deep Learning, AI, Natural Language Processing, or Computer Vision
• Experience with one or more general purpose programming languages, including: Python, Javascript, or similar
• Ability to speak and write in English fluently

Ideally you’d have:

• Have had a previous internship around Machine Learning, Deep Learning, or Computer Vision
• Experience as a researcher, including internships, full-time, or at a lab
• Publications in top-tier journals such as NeurIPS, ICLR, CVPR, AAAI, etc. or contributions to open source projects

The base salary range for this full-time position in San Francisco is $144,000 - $172,800. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

The goal of a Machine Learning Engineer at Scale is to bring techniques in the fields of computer vision, deep learning and deep reinforcement learning, or natural language processing into a production environment to improve Scale's products and customer experience. Our research engineers take advantage of our unique access to massive datasets to deliver improvements to our customers.

We are building a large hybrid human-machine system in service of ML pipelines for Federal Government customers. We currently complete millions of tasks a month, and will grow to complete billions of tasks monthly.

You will:

• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers.

• Take models currently in production, identify areas for improvement, improve them using retraining and hyperparameter searches, then deploy without regressing on core model characteristics

• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines

• Work with massive datasets to develop both generic models as well as fine tune models for specific products

• Build the scalable ML platform to automate our ML service

• Be a representative for how to apply machine learning and related techniques throughout the engineering and product organization

• Be able, and willing, to multi-task and learn new technologies quickly

Ideally You’d Have:

• US citizenship and US Government Security Clearance is a requirement (TS/SCI preferred)

• Extensive experience using computer vision, deep learning and deep reinforcement Learning, or natural language processing in a production environment

• Solid background in algorithms, data structures, and object-oriented programming

• Strong programing skills in Python or Javascript, experience in Tensorflow or PyTorch

Nice to Haves:

• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization

• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment

• Experience with generative AI models

The base salary range for this full-time position in our hub location of Washington DC, is $200,800 - $240,960. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

Scale's Generative AI Data Engine powers the most advanced LLMs and generative models in the world through world-class RLHF/RLAIF, data generation, model evaluation, safety, and alignment.

As the Manager of the Generative AI team, you will be responsible for managing and leading a group of talented researchers and engineers. Your primary focus will be to leverage your expertise in LLMs, generative models, and other foundational models to create and execute an AI roadmap which will help Scale accelerate our customers' Generative AI initiatives forward. This is an exciting opportunity to work on cutting-edge technologies and collaborate with industry-leading professionals.

We are building a large hybrid human-machine system in service of ML pipelines for dozens of industry-leading customers. We currently complete millions of tasks a month and will grow to complete billions monthly.

You will:

• Manage a team of highly effective researchers and engineers. Provide guidance, mentorship, and technical leadership to a team of researchers and engineers working on Generative AI projects. Develop and evaluate methods for integrating machine learning into human-in-the-loop labeling systems to ensure high-quality and throughput labels for our customers.
• Implement and improve on state-of-the-art models developed internally and from the community and put them into production to solve problems for our customers and taskers.
• Work with product and research teams to identify opportunities for improvement in our current product line and for enabling upcoming product lines.
• Work with massive datasets to develop both generic models as well as fine-tune models for specific products.
• Work with customers and 3rd party research groups to understand their goals and define how we can enable them.
• Build a scalable ML platform to automate our ML services, including automated model retraining and evaluation.
• Be able and willing to multi-task and learn new technologies quickly.
• Must be able to commute to the San Francisco Office 1-2x weekly.

Ideally you'd have:

• 7+ years of full time work experience using LLM, deep learning, deep reinforcement learning, or natural language processing in a production environment. Especially training foundational AI models through pre-training, fine-tuning, and RLHF.
• A vision for where the field should go and what Scale should do to enable it.
• Strong programming skills in Python, experience in PyTorch or Tensorflow
• Experience with MLOps and the automation of model training & evaluation
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment
• Solid background in algorithms, data structures, and object-oriented programming
• Deep appreciation for building high-quality, robust, reusable machine-learning software
• Degree in computer science or related field

Nice to haves:

• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Publication experience in the field or related topics.
• Experience with model optimization techniques for both training and inference

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $176,000 - $250,000. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

Scale’s Foundational ML team conducts research on new foundational capabilities, with the goal of innovating models and algorithms that unlock net-new capabilities for Scale’s applied-ML teams and the broader AI community. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s Generative AI team focused on building models to accelerate and optimize AI adoption for some of the largest companies in the world.

At Scale, our research is driven by product needs. Your focus will be on developing new foundational models, algorithms, and forms of supervision for Generative AI. You will lead writing, publishing, and adoption of your work internally with applied teams. You will be involved end-to-end from the inception and planning of new research agendas. You'll be creating high quality datasets, implementing models and associated training and evaluation stacks, producing high caliber publications in the form of peer-reviewed journal articles, blogs, white papers, and internal presentations & documentation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you!

You will:

• Evaluate, adapt, and develop new state of the art language and/or multimodal foundation models
• Work with applied ML and product teams to identify opportunities for service improvement or new capabilities
• Explore approaches that integrate human feedback and assisted evaluation into existing product lines
• Work closely with internal customers to prototype, build, and integrate your models into production service

Ideally you’d have:

• A track record of high-caliber publications in peer-reviewed machine learning venues (e.g. NeurIPS, ICLR, ICML, EMNLP, CVPR, AAAI etc.)
• At least 3 to 5 years of model training, deployment and maintenance experience in a production environment.
• Strong skills in NLP, LLMs and deep learning.
• Solid background in algorithms, data structures, and object-oriented programming.
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.
• Strong high-level programming skills (e.g., Python), frameworks and tools such as Pytorch lightning, kuberflow, TensorFlow, transformers, etc.
• Strong written and verbal communication skills to operate in a cross functional team environment and to broadcast your work efficiently and with splash

Nice to haves:

• Experience in dealing with large scale AI problems, ideally in the generative-AI field.
• Demonstrated expertise in large language models for diverse real-world, production applications, e.g. question-answering, generation, classification, etc.

The base salary range for this full-time position in our hub locations of San Francisco, New York, or Seattle, is $240,000-$280,000. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

Scale's Federal customer base is growing rapidly, and you will be on the front lines of machine learning (ML) operations to accelerate the development of artificial intelligence (AI) applications for the Department of Defense and other national security customers. As Saint Louis Operations Site Lead, you have complete ownership of the outcomes of Scale’s St. Louis AI Center. You will be at the forefront of leading Scale’s Federal labeler workforce and managing site operations across unclassified and classified work sites. This role is for someone who gets excited about leading people, is highly organized, has a strong prioritization ability, can run to ground complex processes with multiple stakeholders, and can develop and grow an organization.

You will:

• Lead a 300+ full time employee and contractor workforce of data quality specialists (labelers) working on unclassified and classified government data
• Oversee site operations across two sites to include recruiting, human resources, security, office management, IT, finance, etc.
• Lead Scale’s growth in STL to potentially doubling over the next 1-2 years
• Own outcomes in their entirety: from ideation and strategy to in-the-weeds delivery of results
• Lead customer-facing presentations on the capabilities and growth of the Saint Louis workforce
• Coach and develop leaders in the workforce to overcome hurdles and achieve high-impact outcomes
• Be a relentlessly positive cultural agent to professionalize the labeler workforce

Ideally you’d have:

• 5+ years of experience in a general manager, operations, growth, or consulting role requiring a blend of operational, strategic, and cross-functional work
• A strong orientation towards outcomes and a history of being scrappy when it counts
• An easygoing interpersonal style and ability to work and build relationships with a wide range of people
• Experience leading small teams and managing multiple, complex work streams
• A fundamental understanding of AI/ML training

Nice to haves:

• MBA or relevant master’s degree
• Background in intelligence work, particularly geospatial analysis
• Active U.S. security clearance (Secret or Top Secret - SCI)

As this role has complete ownership of the outcomes of Scale’s St. Louis AI Center, it is expected to be an onsite-first role. Scale will provide relocation as necessary.

The base salary range for this full-time position in our hub location of St.Louis, Mo is $136,000 - 163,200. Compensation packages at Scale include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Scale employees are also granted Stock Options that are awarded upon board of director approval. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's EEO poster and EEO poster supplement for additional information.

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data.

ABOUT YOU

You have developed ML systems on your own, and are familiar with deploying them in cloud environments. You have solved tough problems across different domains; when challenged with big, new problems you are able to come up with a space of possible solutions, advocate for an approach, and implement seamlessly. You are looking to apply your skills to build new and powerful ML-driven features that will one day be used by digital businesses everywhere. Lastly, you are looking to do this within a small, elite team of product R&D engineers, at a company where we strongly value treating each other well and helping each other succeed.

WHAT YOU'LL BE DOING

• Building the Platform’s Machine Learning Capabilities - We’re building our core ML capabilities from scratch, inspired by open source tools and following basic principles, but tailored to Scuba’s unique behavioral analysis engine. Capabilities we are working on as part of our R&D efforts include in-database AutoML, incremental/online learning, inferencing on data streams, and conversational AI.
• Building New Product Features - We’re building a product unlike any other. Every day we work to solve technical problems in uncharted territory, so that our product can be the best on the market. You’ll be designing, implementing, and maintaining real-time data pipelines and models that enable ML-powered features such as signals discovery, behavioral segmentation, propensity scoring, multi-touch attribution, uplift analysis, and explainability.
• Collaborating - We work with our Engineering, Product, Marketing, Sales, and Customer Success teams to build the best solutions using Scuba’s engine. One of the advantages of being a small startup is that we’re all on a single mission; we have great opportunities to collaborate, share knowledge, and innovate as a team.

SKILLS & KNOWLEDGE

• Bachelor's degree in Economics, Finance, Statistics, Mathematics, Computer Science, Management Information Systems, Engineering, Business Analytics disciplines, or related area; graduate degree preferred.
• 2-6 years of experience working as a Data Scientist / Machine Learning Engineer. Minimum 3 years of experience implementing automated model training and prediction workflows.
• Proficient in Big Data, Python, SQL, TensorFlow and PyTorch. Languages like Go, Rust, Scala, R, and C++ are nice-to-have. Comfortable operating in Linux environments.
• Experience working with data pipelines, real-time systems, and distributed computing.
• Experience building and deploying ML microservices and applications to AWS, Azure and GCP.
• Experience with Large Language Models is great to have.
• Understanding of best practices for machine learning software development, including deployment processes, documentation and coding standards.
• Excellent analytical and problem-solving skills paired with the ability to develop creative and efficient solutions to business problems.
• Ability to lead by envisioning, communicating, influencing and getting things done.
• Experience working in an AGILE development team.

As an Applied Machine Learning Engineer, you’ll research and utilize established and state-of-the-art machine learning (ML) techniques to successfully deliver solutions to our customers. You'll engage new ML use cases through hands-on customer problems and help generalize learnings into the core Snorkel Flow platform. We move fast and are constantly prototyping new ways to deliver value to our customers. The road from A to B isn’t always clear-cut, and the impact of our work is global. Our team is mission-driven and customer-obsessed, and we are looking for an intellectually curious and energetic individual who can replicate this model across our ML initiatives.

Main Responsibilities

• Assist customers with the delivery of a Machine Learning project from beginning to end, including business case definition and scoping, data aggregation and exploration, algorithm selection, and model deployment to deliver business impact to the organization
• Present findings and recommendations to customer stakeholders, assist with program ideation and technical program management, and brief materials.
• Design, develop, and deploy enterprise AI/ML solutions across various industries like finance, healthcare, insurance, retail and more
• Serve as the voice of our customers for new ML paradigms, data science workflows, and share customer feedback to product teams

Preferred Qualifications

• 5+ years of professional experience with machine learning, or 2+ years of professional experience with machine learning with an advanced degree in a relevant field
• 1+ year of professional experience working directly with external customers to scope out build machine learning models, tools, or services
• Expertise in modern machine learning frameworks and technologies (e.g. PyTorch, Transformers, Scikit-learn, NumPy, Pandas), and an obsession with thorough ML evaluation
• Experience building and maintaining large scale, production data pipelines for machine learning applications
• Ability to work in a fast-paced environment and strong technical communication skills

The salary range for our Tier 1 locations of San Francisco, Seattle, Los Angeles & New York is $140,000.00 - $200,000.00.

As an Applied Research Scientist focused on Computer Vision, you will innovate and translate cutting edge research into user experiences. If you find yourself thinking about any of these questions:

• How to leverage LLM agents in conjunction with CV tools to solve CV problems at scale?
• How to build robust foundation models like CLIP with a rich semantic understanding but for detection and segmentation?
• How to solve multi-modal tasks like text-to-image retrieval or image classification in an open-vocabulary setting in expert domains where fine-grained semantic differences matter?
• How to use models like LayoutLM V3 for weakly labeling documents at scale?

We would love to hear from you! More broadly you will work on supervision (self-supervised, semi-supervised, weakly supervised etc) and representation learning methods which result in practical tooling for building and maintaining state-of-the-art machine learning models at scale.

Main Responsibilities

• Establish and empirically demonstrate the state-of-the-art approaches for data-centric model iteration and analysis
• Prototype end-to-end workflows with novel techniques and algorithms, synthesize results, and help to transfer learnings into Snorkel products
• Work closely with design partners to validate your work on real-world use cases with measurable impact
• Contribute to novel research on topics of interest to Snorkel AI by collaborating with other Snorkel Research scientists and affiliate scientists (academic, government, and industry researchers)

Preferred Qualifications

• Broad expertise and understanding of AI, CV, NLP, LLM, and generative AI trends.
• Experience with multi-modal foundation model research at the intersection of image and text
• Experience with training, using and adapting image generation models like stable-diffusion to specific domains
• Experience with model training and inference across a large compute cluster
• Experience with standard machine learning frameworks and tools (NumPy, Scikit-learn, Pandas, Pytorch, TensorFlow, etc.) and machine learning cloud infrastructure and accelerators (AWS, Google Cloud, GPUs and TPUs).
• Strong technical communication skills and the ability to work in a fast-paced environment.
• Experience with developing robust software with excellent coding hygiene and modular design.
• The position involves working with problems with no off-the-shelf solutions and requires innovation on-the-fly. Typically a Ph.D. in machine learning or a related area with good publication history would be a good fit for this position. We would also love to hear from people with similar skill sets acquired through other career paths.

We encourage applications from candidates who believe they satisfy many of the preferred qualifications, even if they do not satisfy all.

At SoundHound, data and engineering are two of our biggest assets. This role lives at the intersection of the two. We aspire to leverage our data to make informed decisions to steer product development, marketing, and user engagement to new heights.

This role is available throughout Canada. Toronto-based employees can work out of our office in downtown Toronto. The compensation package will include salary, equity (RSUs), comprehensive healthcare, paid time off, and other benefits.

In this role, you will:

• Lead and contribute to groundbreaking research in Generative AI, focusing on natural language understanding, dialogue generation, and context-aware conversational systems

• Develop novel algorithms and models for enhancing the performance and intelligence of our conversational AI platform

• Train and fine-tune large-scale deep learning models for natural language processing and dialogue generation

• Collaborate with cross-functional teams, including machine learning engineers, software developers, and product managers, to integrate research findings into our products and solutions

• Provide mentorship and guidance to junior researchers and engineers, fostering a culture of learning and innovation

• Stay up-to-date with the latest advancements in Generative AI and contribute to the continuous improvement of our technology stack

We would love to hear from you if:

• You have a Ph.D. in Computer Science and at least eight years of relevant, full-time industry experience

• You have proven expertise in impactful research and development in Generative AI, with a portfolio of publications and projects demonstrating your expertise

• You are highly proficient in deep learning frameworks (e.g., TensorFlow, PyTorch) and have experience with large-scale model training

• You have in-depth knowledge of natural language processing (NLP) techniques, including pre-trained language models, text generation, and dialogue systems

• You have strong programming skills in Python and can implement and optimize AI models

• You can tackle complex challenges and develop innovative solutions in the field of conversational AI

• You have excellent teamwork and communication skills, with the ability to work effectively with cross-functional teams

• You have a passion for staying at the forefront of AI research and a drive to push the boundaries of what's possible in conversational AI

We’d be especially excited if you have knowledge of reinforcement learning techniques for dialogue systems and conversational AI, have experience working on chatbots or virtual assistants, and have worked at a conversational AI company. Also, please let us know if you have contributed to open-source AI projects and communities!

We strive to be a values-driven company that is supportive of one another, open and honest, undaunted by challenges, nimble and focused, and determined to excel and win.

Here at SoundHound AI, diversity, equity, and inclusion are key to who we are as a company. With a mission to build Voice AI for the world, creating a team with global perspectives is critical to our success.

We care deeply about fostering an environment where everyone is supported and can do their best work. SoundHound ensures that individuals with disabilities are provided reasonable accommodations to participate in the interview process, perform essential job functions, and receive other employment benefits.

Employees enjoy comprehensive health care, paid time off, discounted fitness classes, and flexible working hours. Learn more about our philosophy, benefits, and culture at https://soundhound.com/careers/.

To view our job applicant privacy policy, please visit https://static.soundhound.com/corpus/ta/applicantprivacynotice.html.

Join our growing team and bring your unique voice to our mission!

Working hours

🌎 Given that we are an all-remote company and hire almost anywhere in the world, we don’t have a particular time-zone preference for this role. However, you may need to be available for non-recurring urgent meetings outside of working hours.

Why this job is exciting

We are creating a machine learning team at Sourcegraph, aimed at creating the most powerful coding assistant in the world. Many companies are trying, but Sourcegraph is uniquely differentiated by our rich code intelligence data and powerful code search platform. In the world of prompting LLMs, context is everything, and Sourcegraph’s context is simply the best you can get: IDE-quality, global-scale, and served lightning fast. Our code intelligence, married with modern AI, is already providing a remarkable alpha experience, and you can help us unlock its full potential.

We are looking for a polyglot AI/ML hacker, versed in programming language semantics, with a strong AI/ML background, who can help us deliver the world’s best coding assistant, built on our mature, robust, and open code intelligence platform. And if you happen to have an entrepreneurial streak, you’re in luck: We have an enterprise distribution pipeline, so whatever you build can be deployed straight to enterprise customers with some of the largest code bases in the world, without all the go-to-market hassle you’d encounter in a startup.

You will be a scientist at Sourcegraph Labs doing R&D, and pushing the boundaries of what AI can do, as an IC on our new ML team. You will have the full power of Sourcegraph’s Code Intelligence Platform at your disposal, and you’ll be working on a coding assistant that is already awesome even after just a few weeks of work, so this is a greenfield opportunity to multiply dev productivity to unprecedented levels.

📅 Within one month, you will…

• Start building a trusting relationship with your peers, and learning the company structure.
• Be set up to do local development, and be actively prototyping.
• Dive deep into how AI and ML is already used at Sourcegraph and identify ways to improve moving forward.
• Ship a substantial new feature to end users.

📅 Within three months, you will…

• Be seen as a subject matter expert in all things AI at Sourcegraph.
• Be contributing actively to the world’s best coding assistant.
• Be following all the relevant research, and conducting research of your own.

📅 Within six months, you will…

• Be fully ramped up and owning key pieces of the assistant.
• Be ramped up on other relevant parts of the Sourcegraph product.
• Be helping design and build what might become the biggest dev accelerator in 20 years.

About you

You are a polyglot hacker in the AI/ML space who wants to be part of a world-class team to push the boundaries of AI, with a particular focus on leveraging Sourcegraph’s code intelligence to leapfrog competitors.

First, you have a deep understanding of programming languages, and tools that manipulate code. This could have taken any number of forms; e.g.:

• You’ve worked with grammars and parser generators, or Treesitter
• You’ve worked with compilers and semantic analysis, e.g. type systems
• You’ve written an interpreter, or worked on a virtual machine
• You’ve done static analysis involving scanning source code for semantic information

It doesn’t really matter how you know it, but it’s important that you’re familiar with the basic concepts of semantic representations of source code, and how they’re produced and consumed by tooling.

Second, your AI background could look like a few different things:

• You’ve worked on AI systems and have built ML at large tech companies.
• You have a deep ML background and have demonstrated an ability to be customer and company focused. You are hands-on and can build machine learning
• You are a Prompt Engineer and can take models and figure out how to speak to it in a way that yields different results
• You are an entrepreneurial engineer who can hack together prototypes quickly, get things out the door, and iterate
• You are an LLM hacker or a thought leader in the LLM space and can craft a roadmap that takes advantage of the space, especially with code intelligence
• You’ve worked in NLP or language models at a top-tier research lab

If you’ve been anywhere near the field lately, you can probably pick up enough about LLM capabilities to be able to drive this space, as it’s all greenfield.

Finally, you shouldn’t be a purist about languages. We may need to integrate the coding assistant into a wide variety of tooling contexts, each with its own programming language. You may find yourself writing in several programming languages along the journey, and hopefully you already know most of them a little anyway.

Level

📊 This job is an IC4. You can read more about our job leveling philosophy in our Handbook.

Compensation

💸 We pay you an above-average salary because we want to hire the best people who are fully focused on helping Sourcegraph succeed, not worried about paying bills. You will have the flexibility to work and live anywhere in the world (unless specified otherwise in the job description), and we’ll never take your location or current/past salary information into account when determining your compensation. As an open and transparent company that values equitable and competitive compensation for everyone, our compensation ranges are visible to every single Sourcegraph Teammate. To determine your salary, we use a number of market and data-driven salary sources and target the high-end of the range, ensuring that we’re always paying above market regardless of where you live in the world.

💰 The target compensation for this role is $190,000 USD base.

📈 In addition to our cash compensation, we offer equity (because when we succeed as a company, we want you to succeed, too) and generous perks & benefits.

Interview process [~5.5 hour total interview]

Below is the interview process you can expect for this role (you can read more about the types of interviews in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all!

👋 Introduction Stage - we have initial conversations to get to know you better…

• [30m] Recruiter Screen with Kelsey Nagel
• [45m] Technical Background with Beyang Liu
• [30m] Hiring Manager Screen with Steve Yegge

🧑‍💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team…

• [60m] Resume Deep Dive with Kelsey Nagel
• [45m] Technical Deep Dive with Dominic Cooney and Julie Tibshirani
• [60m] Peer Interview with Erika Rice Scherpelz and Chris Pine
• [Async] Pairing Exercise with the team

🎉 Final Interview Stage - we move you to our final round, where you will gain a better understanding of our business and values holistically…

• [30m] Values Interview
• [30m] Leadership Interview with Quinn Slack
• We check references and conduct your background check

Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process.

Working hours

🌎 Given that we are an all-remote company and hire almost anywhere in the world, we don’t have a particular time-zone preference for this role. However, you may need to be available for non-recurring urgent meetings outside of working hours.

Why this job is exciting

We are creating a machine learning team at Sourcegraph, aimed at creating the most powerful coding assistant in the world. Many companies are trying, but Sourcegraph is uniquely differentiated by our rich code intelligence data and powerful code search platform. In the world of prompting LLMs, context is everything, and Sourcegraph’s context is simply the best you can get: IDE-quality, global-scale, and served lightning fast. Our code intelligence, married with modern AI, is already providing a remarkable alpha experience, and you can help us unlock its full potential.

We are looking for a polyglot AI/ML hacker, versed in programming language semantics, with a strong AI/ML background, who can help us deliver the world’s best coding assistant, built on our mature, robust, and open code intelligence platform. And if you happen to have an entrepreneurial streak, you’re in luck: We have an enterprise distribution pipeline, so whatever you build can be deployed straight to enterprise customers with some of the largest code bases in the world, without all the go-to-market hassle you’d encounter in a startup.

You will be a scientist at Sourcegraph doing R&D, and pushing the boundaries of what AI can do, as an IC on our new ML team. You will have the full power of Sourcegraph’s Code Intelligence Platform at your disposal, and you’ll be working on a coding assistant that is already awesome, so this is a greenfield opportunity to multiply dev productivity to unprecedented levels.

📅 Within one month, you will…

• Start building a trusting relationship with your peers, and learning the company structure.
• Be set up to do local development, and be actively prototyping.
• Dive deep into how AI and ML is already used at Sourcegraph and identify ways to improve moving forward.
• Ship a substantial new feature to end users.

📅 Within three months, you will…

• Be seen as a subject matter expert in all things AI at Sourcegraph.
• Be contributing actively to the world’s best coding assistant.
• Be following all the relevant research, and conducting research of your own.

📅 Within six months, you will…

• Be fully ramped up and owning key pieces of the assistant.
• Be ramped up on other relevant parts of the Sourcegraph product.
• Be helping design and build what might become the biggest dev accelerator in 20 years.

About you

You are a polyglot hacker in the AI/ML space who wants to be part of a world-class team to push the boundaries of AI, with a particular focus on leveraging Sourcegraph’s code intelligence to leapfrog competitors.

First, you have a deep understanding of programming languages, and tools that manipulate code. This could have taken any number of forms; e.g.:

• You’ve worked with grammars and parser generators, or Treesitter
• You’ve worked with compilers and semantic analysis, e.g. type systems
• You’ve written an interpreter, or worked on a virtual machine
• You’ve done static analysis involving scanning source code for semantic information

It doesn’t really matter how you know it, but it’s important that you’re familiar with the basic concepts of semantic representations of source code, and how they’re produced and consumed by tooling.

Second, your AI background could look like a few different things:

• You’ve worked on AI systems and have built ML at large tech companies.
• You have a deep ML background and have demonstrated an ability to be customer and company focused. You are hands-on and can build machine learning
• You are a Prompt Engineer and can take models and figure out how to speak to it in a way that yields different results
• You are an entrepreneurial engineer who can hack together prototypes quickly, get things out the door, and iterate
• You are an LLM hacker or a thought leader in the LLM space and can craft a roadmap that takes advantage of the space, especially with code intelligence
• You’ve worked in NLP or language models at a top-tier research lab

If you’ve been anywhere near the field lately, you can probably pick up enough about LLM capabilities to be able to drive this space, as it’s all greenfield.

Finally, you shouldn’t be a purist about languages. We may need to integrate the coding assistant into a wide variety of tooling contexts, each with its own programming language. You may find yourself writing in several programming languages along the journey, and hopefully you already know most of them a little anyway.

Level

📊 This job is an IC4. You can read more about our job leveling philosophy in our Handbook.

Compensation

💸 We pay you an above-average salary because we want to hire the best people who are fully focused on helping Sourcegraph succeed, not worried about paying bills. You will have the flexibility to work and live anywhere in the world (unless specified otherwise in the job description), and we’ll never take your location or current/past salary information into account when determining your compensation. As an open and transparent company that values equitable and competitive compensation for everyone, our compensation ranges are visible to every single Sourcegraph Teammate. To determine your salary, we use a number of market and data-driven salary sources and target the high-end of the range, ensuring that we’re always paying above market regardless of where you live in the world.

💰 The target compensation for this role is $204,000 USD base.

📈 In addition to our cash compensation, we offer equity (because when we succeed as a company, we want you to succeed, too) and generous perks & benefits.

Interview process [~5.5 hour total interview]

Below is the interview process you can expect for this role (you can read more about the types of interviews in our Handbook). It may look like a lot of steps, but rest assured that we move quickly and the steps are designed to help you get the information needed to determine if we’re the right fit for you… Interviewing is a two-way street, after all!

👋 Introduction Stage - we have initial conversations to get to know you better…

• [30m] Recruiter Screen
• [45m] Technical Background with Beyang Liu
• [30m] Hiring Manager Screen with Steve Yegge

🧑‍💻 Team Interview Stage - we then delve into your experience in more depth and introduce you to members of the team…

• [60m] Resume Deep Dive
• [45m] Technical Deep Dive with Dominic Cooney
• [60m] Peer Interview with Rok Novosel
• [Async] Pairing Exercise with Beyang Liu

🎉 Final Interview Stage - we move you to our final round, where you will gain a better understanding of our business and values holistically…

• [30m] Values Interview
• [30m] Leadership Interview with Quinn Slack
• We check references and conduct your background check

Please note - you are welcome to request additional conversations with anyone you would like to meet, but didn’t get to meet during the interview process.

About this role

We are looking for an experienced Machine Learning Engineer to join our team and play a critical role in improving the empirical best practices surrounding LLM usage, enhancing content personalization, and building out an assessment system to track learner progress. You will work closely with Product teams to design innovative learning experiences and measure the efficacy of production models as they affect our end users. We are a small, dynamic team where you will likely also contribute as a developer and thought partner on broader team projects like ASR, assessment, content personalization, and much more. This is an incredibly exciting time to join an ML team designing a personalized learning experience that will revolutionize language learning for millions of learners worldwide — come join us!

What you'll be doing

• Improving the experimentation best practices around prompt engineering and LLM inference (e.g. A/B testing, metrics and monitoring, evaluation framework)

• Leveraging generative LMs to superpower our content writing and internal tooling

• Working closely with the Product team to enhance our AI-powered lessons

  • adding a memory module, dynamically generating lessons/curriculum, personalizing content based on user interests/learning styles

• Collaborating to build out language assessments and a proficiency tracking system, to measure and communicate progress and to track errors

• Supporting the broader Speech & ML team (e.g. developing and localizing ASR models)

What we're looking for

• Extensive experience training and deploying custom deep learning models to production (experience with NLP and Language Modeling strongly preferred)

• Proficiency in Python and common Deep Learning frameworks like PyTorch

• Strong communication skills and the ability to explain complex ML concepts to non-technical stakeholders

• Sharp product sense and an ability to think broadly and cross-functionally about model quality in the context of user experience

• Bonus

  • Experience in speech or audio

Why work at Speak

1. Join a fantastic, tight-knit team at the right time: we're growing super quickly, we just raised our Series B and an additional extension from some of the top investors in the valley, and we've achieved product-market fit in our initial markets. You'd join at a magical time when a single person could significantly change the course of the company.

2. Do your life's work with people you’ll love working with: we care strongly about our craft and want every person at Speak to feel like they're growing every day. We believe in the idea that working with people you both enjoy and have respect for makes everything better. We hire thoughtfully and only work with people we admire deeply.

3. Global in nature: We're live in over 30 countries and launching in a number of new markets soon. We have dedicated offices in San Francisco, Ljubljana, Seoul, and Tokyo, and you’ll have the opportunity to talk to users in each of these regions on a regular basis as well as travel.

4. Impact people's lives in a major way: Learning a language is one of the single most life-changing skills one can learn, and right now 99% of people never achieve their goal because the process is broken. We’re helping millions of people achieve their goals and improve their lives.

Speak does not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

About this role

We are looking for an experienced Machine Learning Engineer to join our team and help develop cutting-edge phoneme recognition models to provide learners with effective pronunciation feedback. In this role you will take ownership of the end-to-end modeling pipeline, from training and experimentation to deployment and monitoring. You will also work closely with Product teams to design innovative learning experiences and measure the efficacy of production models as they affect our end users. We are a small, dynamic team where you will likely also contribute as a developer and thought partner on broader team projects like ASR, assessment, content personalization, and much more. This is an incredibly exciting time to join an ML team designing a personalized learning experience that will revolutionize language learning for millions of learners worldwide — come join us!

What you'll be doing

• Training and deploying phoneme recognition models end-to-end, including monitoring, performance tracking, and retraining

• Expanding our Pronunciation Coach to provide precise feedback and integrate more broadly across our learning platform

• Tracking metrics to measure performance of existing phoneme models across markets

• Building out an assessment system to provide nuanced feedback on pronunciation, intonation, prosody, and more

• Building and maintaining data infrastructure; i.e. audio data pipelines, training/evaluation datasets creation and management, labeling/active learning loop

• Supporting the broader Speech & ML team (e.g. developing and localizing ASR models)

What we're looking for

• Extensive experience training and deploying custom deep learning models to production (experience with audio/speech strongly preferred)

• Proficiency in Python and common Deep Learning frameworks like PyTorch

• Strong communication skills and the ability to explain complex ML concepts to non-technical stakeholders

• Sharp product sense and an ability to think broadly and cross-functionally about model quality in the context of user experience

• Bonus

  • Experience in speech or phoneme recognition

Why work at Speak

1. Join a fantastic, tight-knit team at the right time: we're growing super quickly, we just raised our Series B and an additional extension from some of the top investors in the valley, and we've achieved product-market fit in our initial markets. You'd join at a magical time when a single person could significantly change the course of the company.

2. Do your life's work with people you’ll love working with: we care strongly about our craft and want every person at Speak to feel like they're growing every day. We believe in the idea that working with people you both enjoy and have respect for makes everything better. We hire thoughtfully and only work with people we admire deeply.

3. Global in nature: We're live in over 30 countries and launching in a number of new markets soon. We have dedicated offices in San Francisco, Ljubljana, Seoul, and Tokyo, and you’ll have the opportunity to talk to users in each of these regions on a regular basis as well as travel.

4. Impact people's lives in a major way: Learning a language is one of the single most life-changing skills one can learn, and right now 99% of people never achieve their goal because the process is broken. We’re helping millions of people achieve their goals and improve their lives.

Speak does not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

About the role:

We are looking for Machine Learning Engineers to work on our audio team who are passionate about generative models and creative applications of AI. In particular, we are looking for people who have experience of developing model serving pipelines to operate at scale and have knowledge of state of the art techniques for optimisation and feature development. We want highly creative ML engineers who are motivated to push the boundaries of generative audio models. You will have access to state-of-the-art high performance computing resources and you will be able to work alongside top researchers and engineers to truly make an impact in the fast growing world of generative AI.

Responsibilities:

• Lead efforts to drive the design, development and production of customer-facing ML music, speech and audio generation systems, with specific reference to inference and API environments
• Work with the Audio, Platform and Inference teams on building pipelines for the next generation of models, where you may assist with areas such as optimization, model tuning and deployment, HPC clusters, and tooling
• Be a strategic thought partner for leaders across the organization on driving business impact through machine learning
• Work on the commercial side - productionizing generative models, and building the infrastructure to serve them at scale
• Produce events and metrics in our data warehouse so that we can analyze critical business metrics like cost, performance, reliability, etc.
• Be part of the team that brings new Stability audio models and pipelines into existence for API customers
• Prototype and productionize inference platform improvements and new features

Qualifications:

• 5+ years working on machine learning projects, including inference and pipeline development
• Solid knowledge of Python scientific stack, PyTorch and at least one high-performance inference framework (e.g. TensorRT)
• Experience profiling and optimizing deep neural networks, including knowledge of GPU profiling tools such as NVIDIA Nsight
• Experience with Python audio processing libraries such as librosa, torchaudio, or similar
• Experience with cloud orchestration systems such as Kubernetes and cloud providers such as AWS, GCP, and Azure
• Ability to rapidly prototype solutions and iterate on them with tight product deadlines
• Experience with training and/or deploying ML models with Amazon AWS (Sagemaker a plus) or Google Cloud
• Strong communication, collaboration, and documentation skills
• Experience with Linux and command line tools
• Evidence of interest in music / audio projects is valued

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the Role:

We are looking for ML Research Engineers who are passionate about generative models for music creation. In particular, we are looking for people who can explore new ideas and architectures for music generation models; highly creative people who straddle research and engineering and who are motivated to push the boundaries of generative music research, not just in state-of-the-art performance, but also in balancing performance and resource usage. You will have access to state-of-the-art, high-performance computing resources, and you will work alongside top researchers and engineers to truly make an impact in the fast growing world of generative AI.

Responsibilities:

• Work with the rest of the research team and the open-source community on developing the next generation of generative audio models
• Prototype and productionize model architecture improvements and new features
• Maintain and innovate on open-source code repositories for generative AI audio models, including custom model code, training code, and fine-tuning code
• Work with Product, Engineering and Commercial teams on model deployment and customized training
• Create interactive demos and interfaces for generative models, demonstrating simple use cases in an intuitive and fun way
• Optimize model architectures and inference code for performance on consumer devices
• Publish results at top conferences, in journals, and in blog posts
• Keep up to date with the latest research advancements in the field and work them into open-source repos, reimplementing as needed to ensure an open license

Qualifications:

• 3+ years working on machine learning projects, including training, fine tuning and refining models
• Publication of papers, projects, and blog posts that had a high impact in generative AI
• Experience maintaining high-quality, well-documented open-source code repositories for AI models
• Experience with music generation models, preferably working in the time domain (Jukebox, SampleRNN, RAVE, etc.)
• Ability to iterate quickly on public code-bases with attention to backwards compatibility, usability, and readability
• Experience with Python scientific stack, PyTorch, and creating Jupyter/Colab notebooks
• Ability to communicate machine learning concepts and results effectively through writing and visualization
• Experience training and/or deploying ML models with Amazon AWS (Sagemaker a plus) or Google Cloud
• Experience with data engineering, including cleaning and maintaining large heterogeneous datasets
• Experience building interactive web demos that serve generative ML models
• Experience with the open-source ML ecosystem (HuggingFace, W&B, etc.)
• Experience with Linux and command line tools
• Familiarity with digital signal processing and audio engineering concepts
• Experience with Python audio processing libraries such as librosa, torchaudio, or similar

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the role:

We are looking for experts in Machine Learning and 3D Graphics, who are passionate about generative models and creative applications of AI. In particular, we are looking for people who share our mission of open-sourcing machine learning models; people who do not believe AI models should be controlled by a centralized gatekeeper behind a closed wall, but rather be truly open and in control by all. You will have access to state-of-the-art high performance computing resources and you will work alongside other creative, hard-working top researchers and engineers, to make a lasting, positive impact in the fast-growing world of generative AI.

Responsibilities:

• Contribute to the creation and improvement of applications and use cases such as text-to-3D, 2D-to-3D, text-to-4D, simple and fast 3D editing… and make systematic progress towards enabling anyone to easily and quickly create complex, animated and interactive 3D characters and environments
• Take ownership of ML and 3D graphics new and existing features, across the whole product lifecycle, from developing prototypes, to assisting the teams charged with production and maintenance - with minimal supervision
• Collaborate within Stability and in the open-source community on developing the next generation of 3D-aware neural models, where you may assist with areas such as optimization of model training, model tuning, dataset engineering, automation of processes, tooling, data translation, integration in game engines, etc.
• Always look for opportunities to delight our customers and improve their life through AI
• If you want: publish new ideas on arxiv and in major conferences

Qualifications:

• 3+ years working on state-of-the-art ML or 3D graphics projects (ideally both), including training, fine-tuning ML models, neural graphics, raytracing, etc.
• Experience researching and implementing SOTA algorithms related to ML or 3D, e.g Neural Radiance Fields, real-time 3D graphics, diffusion models, 3D file format conversion, etc.
• Experience with Python scientific stack, PyTorch or similar ML frameworks
• Communicate ML insights and results effectively: verbally, in writing and through visualization
• Self-motivated, well-organized (e.g. keep track of your own priorities and refine the plan according to new insights), self-reliant (able to debug complex issues with minimal supervision)

Desirable but optional:

• ML and 3D open-source projects or influential publications
• Performance optimization, such as profiling shaders and/or ML systems, C++/CUDA, algorithmic improvements, ML quantization and distillation
• 3D graphics and game development, e.g. OpenGL, DirectX, Vulkan, Unreal Engine, Unity, Godot
• JAX, TPUs, compiler development

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the role:

We are looking for Machine Learning engineers who are passionate about generative models and creative applications of AI. In particular, we are looking for people who share our mission of open-source machine learning models; people who do not believe AI models should be controlled by a centralized gatekeeper behind a closed wall, but rather be truly open and in control by all. We want highly creative ML engineers who are motivated to push the boundaries of generative models. You will have access to state-of-the-art high performance computing resources and you will be able to work alongside top researchers and engineers to truly make an impact in the fast growing world of generative AI.

Responsibilities:

• Lead efforts to drive the design development and production of ML systems, and present the solutions to customers
• Work with Research team on developing the next generation of models, where you may assist with areas such as optimization of model training, model tuning, dataset engineering, HPC clusters, tooling, and work on open-source efforts
• Be a strategic thought partner for leaders across the organization on driving business impact through machine learning
• Work on the Commercial side - productioning generative models, and building the infrastructure to serve them at scale, or work to build customized models for commercial applications
• Prototype and productionize model architecture improvements and new features

Qualifications:

• 3+ years working on machine learning projects, including training, fine tuning and refining models
• Experience with Python scientific stack, PyTorch, creating Jupyter/Colab notebooks
• Experience with JAX / TPUs / CUDA-level / JavaScript (TensorFlow.js etc) a plus
• Ability to communicate machine learning concepts and results effectively through writing and visualization
• Experience with training and/or deploying ML models with Amazon AWS (Sagemaker a plus) or Google Cloud
• Experience with building interactive web demos that serve generative ML models
• Experience with the open-source ML ecosystem (HuggingFace, W&B, etc.)
• Experience with Linux and command line tools

About the role:

We are looking for Research Scientists in the machine learning discipline who are passionate about generative models and creative applications of AI. In particular, we are looking for people who share our mission of open-source research; people who do not believe AI models should be controlled by a centralized gatekeeper behind a closed wall, but rather be truly open and in control by all. We want highly creative researchers who are motivated to push the boundaries of generative models research, not just in state-of-the-art performance, but in pushing the efficient frontier between performance and resource usage. You will have access to state-of-the-art high performance computing resources and you will be able to work alongside top researchers and engineers to truly make an impact in the fast growing world of generative AI.

Responsibilities:

• Work with research team to execute research agenda
• Build the next generation of creative generative AI models
• Publication of results at top conferences or journals, and blog posts
• Work with open-source community on model release and tooling
• Work with engineering / business teams on model deployment and customized training

Qualifications:

• Publication of papers, projects, and blog posts that had a high impact in generative AI
• Experience with dataset curation, rather than rely solely on spoonfed research datasets
• Ability to communicate research ideas effectively through writing and visualization
• Experience with Python scientific stack, PyTorch, creating Jupyter/Colab notebooks
• Experience with training large models on a compute cluster environment is a plus

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the role:

We are seeking a highly motivated and detail-oriented Safety Researcher to join our team. The Safety Researcher will play a crucial role in ensuring the safety and well-being of our organization, employees, and customers. This role involves conducting in-depth research, analyzing safety data, and developing strategies to mitigate risks and promote a secure work environment.

Responsibilities:

• Safety Analysis: Conduct comprehensive research and analysis of safety-related data, incidents, and trends. Identify potential hazards, risks, and areas for improvement.
• Regulatory Compliance: Stay up-to-date with local, state, and federal safety regulations and standards. Ensure the organization’s adherence to all safety-related requirements.
• Safety Procedures: Develop and implement safety policies, procedures, and protocols. Collaborate with various departments to ensure consistent safety practices.
• Risk Assessment: Perform risk assessments to evaluate potential safety hazards and recommend corrective actions. Proactively identify and mitigate safety risks.
• Data Collection: Gather and maintain safety-related data, incident reports, and documentation. Utilize data to drive evidence-based decision-making.
• Training and Awareness: Organize and facilitate safety training programs for employees. Promote safety awareness and best practices throughout the organization.
• Emergency Response: Develop and maintain emergency response plans and protocols. Coordinate drills and exercises to ensure preparedness.
• Reporting: Prepare regular reports on safety performance, incidents, and compliance. Communicate findings to management and make recommendations for improvements.
• Collaboration: Collaborate with cross-functional teams, safety committees, and external agencies to achieve safety objectives.

Qualifications:

• Proven experience in safety research, risk assessment, and safety management.
• Knowledge of safety regulations and standards.
• Strong analytical and problem-solving skills.
• Excellent communication and presentation abilities.
• Detail-oriented with a commitment to accuracy.
• Ability to work independently and as part of a team.
• Certification in safety management (e.g., Certified Safety Professional) is a plus.
• Bachelor’s degree in Safety Management, Occupational Health and Safety, or a related field (Master’s degree preferred).

Personal Attributes:

• Passion for safety and a commitment to creating a secure work environment.
• Proactive and results-driven.
• Strong ethical and professional integrity.
• Ability to adapt to changing circumstances and priorities.

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the role:

We are looking for a versatile ML Engineer who will train and deploy generative models for Japanese partners, clients, and the broader community. You will adapt quickly as we try various approaches to various industries in a fast-changing environment. We will focus especially on image/video models, large language models, and chatbots.

You will have access to state-of-the-art high-performance computing resources and you will be able to work alongside top researchers and engineers to truly make an impact in the fast-growing world of generative AI.

Responsibilities:

• Lead efforts to drive the design, development, and productionization of ML models and systems, and present the solutions to partners and clients in Japan
• Work on the commercial side - productionizing generative models and building the infrastructure to serve them at scale; collaborate with other engineers and researchers to build customized models for commercial applications
• Be a strategic thought partner both internally and externally on driving business impact through machine learning
• Conduct experiments on e.g. fine-tuning image generation models or LLMs for the Japan market
• Prototype and productionize model architecture improvements and new features
• Provide technical advice to partners/clients on generative models

Qualifications:

• Good communication skills with fluency in Japanese and business-level English proficiency
• 5+ years working on machine learning projects, including training, fine tuning and refining models
• Familiarity with recent, important papers and projects in the generative machine learning space
• Experience with Python scientific stack, PyTorch, creating Jupyter/Colab notebooks
• Experience with the open-source ML ecosystem (HuggingFace, W&B, etc.)
• Experience with training and/or deploying ML models with Amazon AWS (Sagemaker a plus) or Google Cloud
• Experience with Linux and command line tools

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

About the role:

We are looking for a talented MLOps Engineer with a focus on Deep Learning and High-Performance Computing that will work with a growing multidisciplinary team of talented research scientists and machine learning engineers to improve and scale the efficiency within our computing capacity.

Responsibilities:

Optimizing Deep Learning Workflows:

• Monitor reports and dashboards and detect low utilization jobs, projects, users
• Partner with researchers to check their workflow when they lack performance
• Identify bottlenecks and suggest scripting optimisations
• For high-scale jobs, introduce AWS proprietary profiler and libraries to boost performance
• Scale-up gating process: check the scripts performance and vet requests to scale up
• Build a knowledge base / best practices documentation for all researchers
• Implement and monitor CPU usage levels for our CPU clusters; identify users that need assistance in properly coding to maximize usage of CPU’s
• Train researchers on best practices on how to implement automatization strategies to minimize human oversight on jobs.

Develop and Test Strategies for Future Workloads:

• Benchmark new systems capabilities and identify strategies to properly utilize them (H100, TRN2, TPUv5, Intel Gaudi)
• Define the minimum needs for storage speeds and find better data loading strategies to support high processing demands of the new accelerators

High-Performance Computing:

• Maintain HPC cluster operations
• Monitor dead nodes and recover them; document dead nodes and their fixes
• Monitor shared volumes health, usage, and clean-up needs, pursue users to clean-up
• Partner with users that do not adequately use POSIX permissions on shared storage
• Monitor the HPC Help Center and solve user problems
• Assist users in properly launching their jobs
• Maintain the future S3 access permissions, debug problems, etc
• Monitor all CPU clusters for users
• Create and maintain processes around authentication, authorization and accounting for clusters usage
• Develop processes around security aspects of the HPC clusters, including tools to in case of security risks are identified (globally, by user, by team, by location, etc)
• Convert and deploy SLURM scheduling for all clouds and all resource types; integrate TPUs into our larger enterprise approach when SLURM becomes available.
• If needed to use k8s infrastructure for research, then maintain SLURM on top of K8S
• Solve SLURM support tickets with Sched MD's bug management tools
• Maintain AWS resources associated with the HPC clusters (login nodes, S3 buckets, FSx volumes, VPCs, subnets, NAT Gateways, S3 VPC Endpoints, routing tables)

Qualifications:

• At least 8+ years of relevant experience
• Applied programming experience in Python, C, and/or C++
• Experience with libraries and tools like PyTorch and CUDA
• Experience in building, productizing and monitoring orchestration pipelines for AI and Machine Learning pipelines
• Experience with training frameworks like Megatrong, NVIDIA or similar frameworks
• Experience in leading more junior engineers
• Experience with AWS and/or GCP
• Experience/exposure to CI tools infra tools is a nice to have (Kubernetes)
• Experience with Linux-based environments and scripting (Shell Scripting, Python, Powershell)
• Ability to work well as an individual contributor as well as within a multidisciplinary team environment
• Strong communicator with excellent interpersonal skills and can-do attitude to work and thrive in a fast-paced team environment

Equal Employment Opportunity:

We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or other legally protected statuses.

Our tech stack includes GCP, Kubernetes, Golang, Python, React, C++, TypeScript, JavaScript, Swift, Kotlin, gRPC, and GraphQL.

What will you do everyday?

You will address the computational infrastructure with your knowledge and prior experience in ASR & NLP techniques and make improvements to our current processes. You will work directly on the platform that powers our microservices. You’ll help scale our platform for thousands of doctors and help improve usability. You’ll implement a microservices architecture and you’ll use Go to do it all. And you’ll be magnificent.

Ok, you're sold, but what are we looking for in the perfect candidate?

• Expertise: You know how to code. You understand our tech stack and can be productive with it. In other words, you’ve done this before.
• Action oriented: You love to build. You like to ship fast and quickly iterate.
• Creativity: You enjoy listening to user feedback and then building products in novel ways. You’re resourceful and enjoy finding alternate paths to success.
• Problem solving: you use data to help point you in the correct direction. You optimize relentlessly. You think business and engineering problems are like puzzles and you stick with them until they are solved.
• Humility: You’re humble and love working in a team without ego to deliver products
• Adaptability: You thrive in a fast-moving organization that uses light-weight processes and cutting-edge technology to have a huge impact.
• Confidence: You trust your abilities and you’re ready to push yourself to the next level.
  
  
  
  
  

Requirements*

• Proficient in C++/Python
• 5+ years in overall Machine Learning experience, with at least three years focused on ASR
• Proven record of an end to end workflow and ASR (Automated Speech Recognition) experience .
• Expert in the understanding, practice, and deployment of deep neural network models.
• Proven ability to build and maintain distributed backend services for ML/AI Applications
• Experience taking product technical design from inception to production
• Strong grasp of CS fundamentals including algorithms, data structures and design is preferred

*Requirements is such a strong word. We don’t necessarily expect to find a candidate that has done everything we’ve listed, but you should be able to make a credible case that you’ve done most of it and are ready for the challenge of adding some new things to your resume.

Tell me more about Suki

• On a roll: Named by Forbes as one of the top 50 companies in AI; named "Best New Startup" by Rock Health; announced a major partnership with Google.
• Great team: Founded, managed, and backed by successful tech veterans from Google and Apple and medical leaders from UCSF and Stanford. We have technologists and doctors working side-by-side to solve complex problems.
• Great investors: We’re backed by Venrock, First Round Capital, Marc Benioff, and others. With our $55M Series C financing, we have the resources to scale.
• Huge market: Disrupting a massive, growing $30+ billion market for transcription, dictation, and order-entry solutions. Our vision is to become the voice user interface for healthcare, relieving the administrative burden on doctors instead of adding to it.
• Great customers: Help our doctors save time on data entry so they can focus on providing excellent care.
• Impact: You’ll make an impact from day one. You’ll join a team working towards a shared purpose with a culture built upon deep empathy for doctors and passion for making their lives better.

Suki is an Equal Opportunity Employer. We are dedicated to building a company that fosters inclusion and belonging and reflects the diverse communities we serve across the country. We know we are stronger this way, and we look forward to growing our team with these shared values.

About the role

We are looking for an experienced Machine Learning Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release.

👩‍💼 You will join a group of more than 40 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner.

If you know and love VALL-E, TorToise, Voicebox, SPEAR-TTS, MusicLM and more - and you love machine learning and large data, then we would love to talk to you. We will also want to talk to you - if that's what you dream of doing. 🤩

What will you be doing?

🚀 In this position, you'll join the team to help develop our LLM-based TTS system that will provide our customers with voice clones that are indistinguishable from real voices. You will also help us create high quality, production ready code and take ownership of production pipelines. This would include:

• Taking hypotheses, ideas or papers and creating implementations of solutions on the back of these.
• Running experiments on the back of the created implementations to evaluate and verify your hypotheses.
• Enhancing model training and inference optimisation to ensure efficient and accurate results.
• Contributing to a high-quality codebase, developing tests where necessary, and participating in code reviews.
• Helping a team of Research engineers and Scientists to write clean and efficient code, and define best practices.
• Taking ownership of the full ML lifecycle from concept, development, testing, validation to deployment.
• Developing production quality software, our teams work “full stack” with the ability to deliver direct to product and impact the world.
• Optimising for deployment - turning prototypes into working solutions.

Who are you?

• You have a background in Computer Science and 5+ years of relevant experience.
• You have substantial experience working with and training Large Language Models on sizeable clusters, applying this knowledge to practical scenarios.
• You have experience in scaling large models via model parallelism multi-node training and other techniques such as sharding and distillation.
• You demonstrate excellent Python coding skills and have a deep interest in the software development aspect of ML.
• You possess a research-oriented mindset, constantly exploring new techniques and solutions, and are adept at finding what works best in a given scenario.
• And finally..You have excellent verbal and written communication skills and you are passionate about what you do!

Nice to have…

• Advanced expertise in PyTorch, with a deep understanding of its distributed and parallel approaches, as well as the related tools and frameworks.
• Proficiency in state-of-the-art frameworks like DeepSpeed and OpenAI Triton, with proven experience leveraging these tools to optimize and accelerate ML model training and inference.
• Extensive experience with AWS, including a strong understanding of its various services and how they can be integrated for robust, scalable ML solutions.

The good stuff...

💸 You will be compensated well (salary + stock options + bonus)

📍 You will work in a hybrid setting with an office in London

🚲 You get a cycle to work salary sacrifice scheme to commute to the office

🏝 You get 25 days of annual leave + public holidays

🥳 You will join an established company culture with regular socials and company retreats

🤩 You get 4 weeks paid sabbatical after 4 years at the company + $10,000!!

👉 You can participate in a generous referral scheme

🚀 You will have huge opportunities for your career growth

You can see more about Who we are and How we work here: https://www.synthesia.io/careers

About the role

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to push the boundaries and uncover brand new solutions to challenging problems in the AI field. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in the domain of multiple view geometry and non-rigid motion tracking.

👩‍💼 You will join a group of more than 40 Researchers and Engineers in the R&D department. We are building a world class 4D capture facility and we want You to help us find the best way to do this! You will be working to deliver state-of-the-art solutions to track everything for humans in motion (face, body, hands, clothing, hair) in both monocular and multi-view video.

Our research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner. This is an open, collaborative and highly supportive environment. We are all working together to build something big - the future of synthetic media and programmable video through Generative AI. We are proud of the culture, as well as the impact of the technology we are building.

What will you be doing?

🚀 In this position, you will join our R&D team working on introducing state-of-the-art solutions for human tracking. We have built a modern volumetric capture studio with x80 24MP cameras, x300 lights, motion control platform and an amazing production crew which you will engage with on a daily basis! In this role you will:

• Join the team to build a state-of-the-art human tracking capability.
• Work on capturing high resolution, high fidelity, photo-real digital humans
• Build a pipeline for accurate tracking of the face, body, hands surface of humans in motion
• Support the production and delivery of high quality data-sets.
• Implement data pipelines for image and geometry data processing.
• Implement fast data processing pipelines for human tracking in multi-view video.
• Develop production quality code to implement methods into working systems.
• Support and develop best practises in development across the team.
• Own the full lifecycle from concept, data, code, experiment to delivery.

Who are you?

We are looking for experienced Research Engineers, someone who knows how to deliver practical solutions and thrives working in a busy start-up environment!

If you are a domain expert on monocular and multi-view tracking, if you know the state-of-the-art and would be able to define how we address hand tracking - then we want to talk to you! We'd also love to talk to you - if this is what you dream of doing. 😎

You will have:

• 3+ years industry experience in Computer Vision (incl. Motion Tracking). Having a related PhD is an advantage!
• Practical Experience and strong knowledge of Geometry tracking (ideally for humans).
• Experience in 3D computer vision and Computer graphics, you understand multiple view geometry.
• Experience dealing with / setting up large Data-sets.
• Excellent coding skills in Python - our teams work full-stack, you will deliver solutions from a concept to production-ready code.
• Experience with most modern frameworks for deep learning (PyTorch) as well as for software development (Git, Linux).
• Outstanding communication skills.

Nice to have…

• Experience with Hand-tracking from multi-view or monocular data.
• Experience representing Hair - hair geometry and appearance from multi-view images.
• Experience with C++ / CUDA.

The good stuff...

💸 You will be compensated well (salary + stock options + bonus)

📍 You will work in a hybrid setting with an office in London

🚲 You get a cycle to work salary sacrifice scheme to commute to the office

🏝 You get 25 days of annual leave + public holidays

🥳 You will join an established company culture with regular socials and company retreats

🤩 You get 4 weeks paid sabbatical after 4 years at the company + $10,000!!

👉 You can participate in a generous referral scheme

🚀 You will have huge opportunities for your career growth

You can see more about Who we are and How we work here: https://www.synthesia.io/careers

About the role

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to push the boundaries and uncover brand new solutions to challenging problems in the AI field. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in the domain of multiple view geometry and non-rigid motion tracking.

👩‍💼 You will join a group of more than 40 Researchers and Engineers in the R&D department. We are building a world class 4D capture facility and we want You to help us find the best way to do this! You will be working to deliver state-of-the-art solutions to track everything for humans in motion (face, body, hands, clothing, hair) in both monocular and multi-view video.

Our research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner. This is an open, collaborative and highly supportive environment. We are all working together to build something big - the future of synthetic media and programmable video through Generative AI. We are proud of the culture, as well as the impact of the technology we are building.

What will you be doing?

🚀 In this position, you will join our R&D team working on introducing state-of-the-art solutions for human tracking. We have built a modern volumetric capture studio with x80 24MP cameras, x300 lights, motion control platform and an amazing production crew which you will engage with on a daily basis! In this role you will:

• Join the team to build a state-of-the-art human tracking capability.
• Work on capturing high resolution, high fidelity, photo-real digital humans
• Build a pipeline for accurate tracking of the face, body, hands surface of humans in motion
• Support the production and delivery of high quality data-sets.
• Implement data pipelines for image and geometry data processing.
• Implement fast data processing pipelines for human tracking in multi-view video.
• Develop production quality code to implement methods into working systems.
• Support and develop best practises in development across the team.
• Own the full lifecycle from concept, data, code, experiment to delivery.

Who are you?

We are looking for experienced Research Engineers, someone who knows how to deliver practical solutions and thrives working in a busy start-up environment!

If you are a domain expert on monocular and multi-view tracking, if you know the state-of-the-art and would be able to define how we address hand tracking - then we want to talk to you! We'd also love to talk to you - if this is what you dream of doing. 😎

You will have:

• 3+ years industry experience in Computer Vision (incl. Motion Tracking). Having a related PhD is an advantage!
• Practical Experience and strong knowledge of Geometry tracking (ideally for humans).
• Experience in 3D computer vision and Computer graphics, you understand multiple view geometry.
• Experience dealing with / setting up large Data-sets.
• Excellent coding skills in Python - our teams work full-stack, you will deliver solutions from a concept to production-ready code.
• Experience with most modern frameworks for deep learning (PyTorch) as well as for software development (Git, Linux).
• Outstanding communication skills.

Nice to have…

• Experience with Hand-tracking from multi-view or monocular data.
• Experience representing Hair - hair geometry and appearance from multi-view images.
• Experience with C++ / CUDA.

The good stuff...

💸 You will be compensated well (salary + stock options + bonus)

📍 You will work in a hybrid setting with an office in Munich, Germany

🏝 You get 25 days of annual leave + public holidays

🥳 You will join an established company culture with regular socials and company retreats

🤩 You get 4 weeks paid sabbatical after 4 years at the company + $10,000!!

👉 You can participate in a generous referral scheme

🚀 You will have huge opportunities for your career growth

You can see more about Who we are and How we work here: https://www.synthesia.io/careers

About the role

We are looking for a Research Engineer, with passion for working on cutting edge problems that can help us create highly realistic, emotional and life-like synthetic humans through text-to-video.

Our aim is to make video content creation available for all - not only to studio production!

🧑🏼‍🔬 You will be someone who loves to code and build working systems. You are used to working in a fast-paced start-up environment. You will have experience with the software development life cycle, from ideation through implementation, to testing and release. You will also have extensive knowledge and experience in Computer Vision and Generative AI domain.

👩‍💼 You will join a group of more than 40 Engineers in the R&D department and will have the opportunity to collaborate with multiple research teams across diverse areas, our R&D research is guided by our co-founders - Prof. Lourdes Agapito and Prof. Matthias Niessner.

If you know and love DALL.E, MUSE, IMAGEN, MAKE-A-VIDEO, STABLE DIFFUSION and more - and you love large data and large compute, then we would love to talk to you.

What will you be doing?

🚀 In this position, you'll join the team to help develop our foundational model for video generation based on large video data-sets. You will also help build the academic contributions in this area. In this role you will be conducting cutting edge research, pushing the boundaries and going beyond existing SOTA solutions. This would include:

• Reviewing specialised literature on text to video / video synthesis.
• Designing the requirements, project scoping and owning the roadmap in your area.
• Managing the progress of the Large Video Model project and making sure that it is in line with our vision.
• Building libraries to accelerate our iteration speed during development (abstracting common functionality, automating tests sweeps, visualising results etc.).
• Developing production quality software, our teams work “full stack” with the ability to deliver direct to product and impact the world.
• Taking ownership of the full ML lifecycle from concept, development, testing, validation to deployment.
• Adapting off-the-shelf solutions for the purposes of our product.
• Optimising for deployment - turning prototypes into working solutions.

Who are you?

• You have a background in Computer Vision / Computer Science and 3+ years of relevant experience.
• You have researched / worked with Generative Models (incl. Diffusion models) - you know all the best practices and approaches.
• You are interested in doing research, trying new things and pushing the boundaries, going beyond what's already known.
• You have experience in using most modern frameworks for machine learning and deep learning.
• You have great coding skills in Python and you care about writing beautiful code.
• And finally..You have excellent verbal and written communication skills and you are passionate about what you do!

Nice to have…

• Multi-GPU Multi-Node compute.
• Open source contributors.
• Computer graphics.
• CI/CD practices.
• Strong background in Maths.

The good stuff...

💸 You will be compensated well (salary + stock options + bonus)

📍 You will work in a hybrid setting with an office in London

🚲 You get a cycle to work salary sacrifice scheme to commute to the office

🏝 You get 25 days of annual leave + public holidays

🥳 You will join an established company culture with regular socials and company retreats

🤩 You get 4 weeks paid sabbatical after 4 years at the company + $10,000!!

👉 You can participate in a generous referral scheme

🚀 You will have huge opportunities for your career growth

You can see more about Who we are and How we work here: https://www.synthesia.io/careers

As a Machine Learning Engineer at TeachFX, you'll be a key leader of our company as we scale, and you’ll help define TeachFX’s engineering culture. You’ll build the systems that will support our growth, and will have the ability to take ownership of projects from inception to completion. We are a deeply mission-driven company, working hard to develop tech that revolutionizes teacher professional learning -- and we’re looking for engineers who want to use their skills to power our mission.

Primary Responsibilities:

• Develop, test, and deploy machine learning models tailored for classroom interactions.

• Collaborate with the product team to integrate AI capabilities into the platform.

• Continuously monitor and refine models to ensure optimal performance.

• Translate vast classroom data into actionable insights.

• Work closely with the tech and educational teams, ensuring models align with pedagogical needs.

• Stay updated with the latest in machine learning and AI research

You might be a good fit if:

• You have 2+ years of industry software engineering experience.

• You have a solid foundation in machine learning, deep learning, and AI.

• You have experience in deploying models in real-world applications.

• You have proficiency in Python and familiarity with ML frameworks like TensorFlow or PyTorch.

• You have exceptional problem-solving skills and are eager to collaborate with other team members

• You have strong communication skills – capable of explaining complex concepts to non-technical stakeholders.

• You are goal-oriented, with an emphasis on results.

• You are adaptable and open to feedback.

• You are passionate about social impact and education. You are excited to have an impact on tens of millions of kids' lives through your work.

Our tech stack: We use Airflow, Vertex AI, PyTorch, Docker, BigQuery, Data Studio, and other Google Cloud Platform services.

TeachFX is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

As a research scientist in machine learning at TeachFX, you'll be a key leader of our company as we scale. You’ll build the systems and technology that will support our growth, drive our research strategy and will take ownership of projects from inception to completion. We are a deeply mission-driven company, working hard to develop tech that revolutionizes teacher professional learning -- and we’re looking for researchers who want to use their skills to power our mission.

Primary Responsibilities:

• Conduct cutting-edge research in machine learning

• Design and prototype new algorithms, enhancing the platform’s ability to interpret and evaluate classroom interactions.

• Collaborate closely with the engineering team to integrate your research findings into the TeachFX platform.

• Analyze classroom data, deriving insights that inform product development and pedagogical strategies.

• Maintain an active presence in the academic community, collaborating with researchers from academic institutions and representing TeachFX at conferences.

• Work closely with our team of educators to ensure the scientific advancements align with on-ground teaching needs.

• Stay abreast of the latest developments in machine learning, particularly as they pertain to education.

Qualifications:

• PhD in Computer Science, Linguistics or equivalent field

• Strong foundation in machine learning, with a focus on real-world applications of ASR or other speech tasks

• Demonstrated ability to conduct independent research, as evidenced by published papers in recognized journals or conferences.

• Expertise in Python and familiarity with machine learning frameworks such as TensorFlow and PyTorch.

• Exceptional problem-solving and analytical skills.

• Collaborative spirit, with the ability to work seamlessly with cross-functional teams.

• Excellent communication skills, capable of conveying complex concepts to non-technical stakeholders.

At TeachFX, we’re not just building a product; we’re crafting the future of education. If you’re excited about the confluence of research, machine learning, and education, then we’d love to hear from you. Join us in redefining the landscape of classroom teaching and learning.

TeachFX is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Responsibilities

• Collaborate with cross-functional teams to understand project requirements and translate them into effective AI solutions.
• Design, implement, and iterate on neural network architectures using PyTorch to achieve optimal performance on diverse tasks.
• Train, validate, and fine-tune machine learning models using relevant datasets to ensure high accuracy and robustness.
• Investigate and troubleshoot model performance issues, iterating on models and techniques to continuously improve results.
• Stay current with the latest research and developments in the field of machine learning and AI, applying relevant advancements to our projects.
• Contribute to the design and implementation of scalable and efficient AI pipelines.
• Work closely with engineers to integrate AI models into production systems.

Experience & Qualifications

• Bachelor's or higher degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• Strong proficiency in Python programming and hands-on experience with PyTorch for developing and training deep learning models.
• Demonstrated experience in designing, training, and deploying neural networks for various applications.
• Solid understanding of machine learning fundamentals, including supervised and unsupervised learning techniques.
• Excellent problem-solving skills and the ability to approach challenges with creativity and a strong analytical mindset.
• Familiarity with debugging techniques and a knack for identifying issues and finding effective solutions.
• Experience with C++ is a plus but not mandatory.
• A self-motivated individual with a strong desire to learn, explore, and excel in a fast-paced, innovative environment.
• Strong communication skills and the ability to work collaboratively in a team setting.

Responsibilities

• Develop novel LLMs and primitives that take advantage of Tenstorrent’s breakthrough accelerator architecture to deliver orders of magnitude performance & efficiency improvements.
• Model benchmarking, Performance Analysis, Characterization on novel hardware accelerator.
• Fine tune/Retrain emerging LLM models after architectural modification to improve performance.
• Implement ideas from latest research papers and validate new optimizations on novel hardware, suggest improvements on the existing ideas and validate new ideas through experiments.
• Implement ML models on Tenstorrent’s PyBUDA Compiler framework and analyze results, suggest novel architectural changes to make them more efficient.

Experience & Qualifications

• Deep understanding of Transformer based model architecture (e.g., BERT, GPT, LLaMA, FALCON) - should be able to analyse performance bottlenecks in training or inference.
• Expertise (through evidence in prior projects or research) in large-scale foundation model (CNN/ Transformer/Generative) training and optimisations including quantisation, pruning, low-rank approximation (e.g., LoRA, SVD), sparsity aware training, early exit models, conditional computing, sparse attentions, NAS, fine-tuning (e.g., RLHF, PEFT)
• Excellent working knowledge of Python, PyTorch or TensorFlow, (optional C/C++ if interested in compiler and software stack)
• Familiarity with and passion for any of the following -- ML compilers, high-performance and massively parallel systems, distributed model training and inference, GPU or AI accelerator architecture -- is a plus.

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Interface closely with the Backend and DevOps teams as well as with our internal data labeling services
• Utilize OWASP top 10 techniques to secure code from vulnerabilities
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics
• You have 1-2 years industry machine learning experience
• You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
• You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others
• You know the ins and outs of Python, especially as it applies to the above ML frameworks
• You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
• You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker
• You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
• You have great communication skills and ability to work with others
• You are a strong team player, with a do-whatever-it-takes attitude

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Interface closely with the Backend and DevOps teams as well as with our internal data labeling services
• Utilize OWASP top 10 techniques to secure code from vulnerabilities
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• You have an undergraduate or graduate degree in computer science or similar technical field, with significant coursework in mathematics or statistics
• You have 1-2 years industry machine learning experience
• You have successfully trained and deployed a deep learning machine model (image, NLP, video, or audio) into production, with measurably improved performance over baseline, either in industry or as a personal project
• You have strong experience with a high-level machine learning frameworks such as Tensorflow, Caffe, or Torch, and familiarity with the others
• You know the ins and outs of Python, especially as it applies to the above ML frameworks
• You are capable of quickly coding and prototyping data pipelines involving any combination of Python, Node, bash, and linux command-line tools, especially when applied to large datasets consisting of millions of files
• You have a working knowledge of the following technologies, or are not afraid of picking it up on the fly: C++, Scala/Spark, SQL, Cassandra, Docker
• You are up-to-date on the latest deep neural net research and architectures, both in understanding the theory and motivations behind the techniques, as well as how to implement them in the ML framework of your choice
• You have great communication skills and ability to work with others
• You are a strong team player, with a do-whatever-it-takes attitude

Responsibilities

• Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
• Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
• Participate in products technical design and architecture
• Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production
• Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
• Implement and manage security protocols such as training, code review, and best practices
• Own and manage the risk and security of your business function in coordination with the Security Team
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• Undergraduate or graduate degree in computer science or similar technical field
• 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
• Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
• 2+ years experience managing machine learning teams
• You have an ability to understand and make well-reasoned tradeoffs in designing features
• Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
• Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
• Have experience collaborating with product managers and labeling team in delivering model improvements

Responsibilities

• Interface closely with product management, engineering, devops, labeling, and sales teams to build roadmap in supporting the long term vision of the team
• Lead a team of highly capable and passionate machine learning engineers, helping them achieve their goals through mentorship
• Participate in products technical design and architecture
• Participate in the full development cycle: data collection, labeling, model development, experimentation, training, testing, and deployment in production.
• Drive delivery for our product milestones, continually releasing model with new well tested features and ensuring quality metrics are achieved
• Implement and manage security protocols such as training, code review, and best practices
• Own and manage the risk and security of your business function in coordination with the Security Team
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• Undergraduate or graduate degree in computer science or similar technical field
• 4+ years experience as a machine learning engineer, with experience in training large deep learning models and working with real world data
• Knowledgeable in at least one focus area of machine learning, such as computer vision, audio, or NLP
• 2+ years experience managing machine learning teams
• You have an ability to understand and make well-reasoned tradeoffs in designing features
• Management skills: ability to set roadmap and goals for a team and its individual members, delegate, mentor, and deliver results
• Have a desire to interview engineers, collaborate with a recruiting team, and smoothly onboarding new team members
• Have experience collaborating with product managers and labeling team in delivering model improvements

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Write and maintain scalable, performant and secure code that can be shared across platforms
• Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, processes and security
• Develop novel, accurate, and performant ML algorithms for use at scale
• Conduct metric-driven research experiments to improve model performance
• Provide mentorship to and help onboard junior ML engineers
• Collaborate cross-functionally with other teams
• Utilize OWASP top 10 techniques to secure code from vulnerabilities
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have a minimum of 5 years of building production scale ML models
• You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
• You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
• You have experience writing code and training across distributed systems
• You have an ability to understand and make well-reasoned tradeoffs in designing features
• You can lead end to end development of new products
• You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
• You strongly believe in high code quality, automated testing, and other engineering best practices
• You have attention to detail and a passion for correctness
• You are comfortable with ambiguity and scoping solutions with your teammates
• You have strong interpersonal and communication skills with a bias towards action

Responsibilities

• Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Write and maintain scalable, performant and secure code that can be shared across platforms
• Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, processes and security
• Develop novel, accurate, and performant ML algorithms for use at scale
• Conduct metric-driven research experiments to improve model performance
• Provide mentorship to and help onboard junior ML engineers
• Collaborate cross-functionally with other teams
• Utilize OWASP top 10 techniques to secure code from vulnerabilities
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have a minimum of 5 years of building production scale ML models
• You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
• You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
• You have experience writing code and training across distributed systems
• You have an ability to understand and make well-reasoned tradeoffs in designing features
• You can lead end to end development of new products
• You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
• You strongly believe in high code quality, automated testing, and other engineering best practices
• You have attention to detail and a passion for correctness
• You are comfortable with ambiguity and scoping solutions with your teammates
• You have strong interpersonal and communication skills with a bias towards action

Responsibilities

• Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Write and maintain scalable, performant code that can be shared across platforms
• Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, and processes
• Develop novel, accurate, and performant ML algorithms for use at scale
• Conduct metric-driven research experiments to improve model performance
• Provide mentorship to and help onboard ML engineers
• Lead cross-functional collaboration with other teams
• Contribute to defining strategic direction, planning the roadmap
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Minimum Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have 8+ years of experience building web applications
• You have successfully implemented highly-available distributed systems/microservices
• You have delivered scalable backend APIs
• You have strong interpersonal and communication skills with a bias towards action
• You have experience writing code and training across distributed systems
• You have the ability to understand and make well-reasoned tradeoffs in designing features
• You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
• You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
• You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
• You can lead end to end development of new products

Responsibilities

• Everything involved in applying a ML model to a production use case, including designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
• Write and maintain scalable, performant code that can be shared across platforms
• Contribute meaningfully to the product and core backend systems by suggesting and executing improvements
• Improve engineering standards, tooling, and processes
• Develop novel, accurate, and performant ML algorithms for use at scale
• Conduct metric-driven research experiments to improve model performance
• Provide mentorship to and help onboard ML engineers
• Lead cross-functional collaboration with other teams
• Contribute to defining strategic direction, planning the roadmap
• Maintain awareness of industry best practices for data maintenance handling as it relates to your role
• Adhere to policies, guidelines and procedures pertaining to the protection of information assets
• Report actual or suspected security and/or policy violations/breaches to an appropriate authority

Minimum Requirements

• You have a Bachelor's Degree in computer science or a related field
• You have 8+ years of experience building web applications
• You have successfully implemented highly-available distributed systems/microservices
• You have delivered scalable backend APIs
• You have strong interpersonal and communication skills with a bias towards action
• You have experience writing code and training across distributed systems
• You have the ability to understand and make well-reasoned tradeoffs in designing features
• You are an expert in machine learning frameworks, such as PyTorch or Tensorflow
• You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
• You are a subject matter expert in at least one focus area of machine learning, such as computer vision or natural language processing
• You can lead end to end development of new products

About the role

Tome is bringing storytelling into the modern era by constantly narrowing the gap between what creators mean to express and what their audiences experience.

The next innovative leap in our journey is adding the latest AI/ML capabilities to Tome's existing magic. To enable that, the team is looking to hire a Lead ML Engineer to build Tome's most magical and amazing features, craft our AI/ML strategy, and build out an outstanding team.

Tome's AI/ML team will be building front-and-center experiences into the product, to bring the next level of wow to our users. There's much innovative work ahead: from generating image, text, and layouts, to enhancing videos, to complete AI story creation.

What you'll do

• Drive large impact on Tome's growth by shipping magical creation experiences that customers are eager to use

• Help drive Tome's AI/ML strategy in tight collaboration with founders and execs

• Identify user needs and product features that are well suited for AI/ML solutions and frame the problems

• Develop prototypes for innovative creation experiences based on generative AI models like GPT-3 and Stable Diffusion and drive development of those into robust product features

• Work closely with product designers to apply AI/ML for creating features that delight users and stimulate and augment creators' imagination

Who you are

• You have a BS or MS degree in CS, AI, or applied math

• You have 2+ years of experience building AI/ML based products or features in NLP or vision domains

• You have a strong understanding of deep learning AI/ML frameworks or cloud services

• You have hands-on ML Ops experience

Bonus Points

• Experiencing leading AI/ML product initiatives• Publications in applied AI/ML scientific journals

$140,000/year to $225,000/year + equity + benefits

Tome Perks:

💰 Compensation & Equity

• We offer competitive compensation & equity packages. At Tome we want you to feel ownership over the work you do and capitalize on the upside you create in the company.

🏝 Unlimited PTO

• Take the time you need to with unlimited vacation days.

🛌 Sick Leave

• Unlimited. Take the days you need to feel your best and do your best work.

👼 Parental Leave

• Tome offers 3 months of paid time off for maternity & paternity leave.

💸 Retirement

• Tome offers a 401k plan through Human Interest

🍱 Weekly Lunch Stipend

• Weekly UberEats credit to order a favorite meal.

🚎 Commuter Benefits

• For those in the Bay Area we offer: up to $25/day in parking ($350 for a monthly pass) & Muni/Bart rides (up to $350/month).

✈️ Travel & Hotel Accommodations for Remote Members

• Quarterly trips to keep remote members connected.

🏩 Prorated Medical Insurance

• Choose the coverage that suits you and your family's needs.

💻 Hardware

• M1 Max MBP laptop of your choice

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

• As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:
• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A phD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Generous equity package

• 23 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

• L&D budget to use on Learnerbly (our learning platform)
• Meal vouchers

#LI-TE1

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

• As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:
• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A phD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Generous equity package

• 23 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

• L&D budget to use on Learnerbly (our learning platform)
• Meal vouchers

#LI-TE1

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

• As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:
• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A phD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Generous equity package

• 23 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

• L&D budget to use on Learnerbly (our learning platform)
• Meal vouchers

#LI-TE1

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

• As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:
• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A phD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Generous equity package

• 23 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

• L&D budget to use on Learnerbly (our learning platform)
• Meal vouchers

#LI-TE1

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:

• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A PhD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Computer vision experience.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Twice a year compensation reviews
• Generous equity package
• 5% employer match on pension

Time off and flexible working

• 25 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Additional leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

Support for your health and wellbeing

• Highest tier of private health coverage through Bupa
• Access to a virtual GP through Babylon
• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

Additional perks

• L&D budget to use on Learnerbly (our learning platform)
• Cycle to Work scheme

Research @ Tractable

Our team shapes the technical foundations used across all Tractable products, currently focused on auto insurance and natural disaster recovery. Our mission is to leverage the latest ML research to solve hard science problems necessary to transform the insurance industry (& more). We focus on creating mission-critical AI systems solving some of the trickiest problems in computer vision, and our innovation has already improved the lives of 100,000s of people so far (really). We’re a fun and ambitious team, and looking for someone to join us on our exciting journey!

Auto organization – Who we are & What we do

Our organization is responsible for building products for the automotive industry. We have already built 2 products (Estimating, Review) sold globally to insurers.

Our long-term vision is to build a platform ecosystem that we can leverage to effortlessly build new products and use cases. Our current mission is to create a reliable and safe “virtual” motor appraiser/expert as a service, we can leverage to solve many use cases across the automotive industry. We are doing so, by building high-quality input capture mechanisms for our users, creating a state-of-the-art damage assessment stack for auto damage, or delivering explainable and human-centric decision-making engines.

We are working hand-in-hand with engineering teams to turn our R&D prototypes into mission-critical systems.

What you will do

• As an Applied scientist, you will contribute to the design, development, and improvement of AI/ML models and systems. You will:
• Work with applied scientists, data scientist, software engineers and product partners to design and deliver AI/ML solutions in production at scale.
• Design and develop AI/ML models, workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML models and systems.
• Deliver customer-facing and/or underlying AI/ML solutions that empower our platform to provide the best experience for our customers.

What you need to be successful
Basic qualifications

• Master's in Computer Science, Machine Learning, or related quantitative field. A phD in Computer Science or related fields with a focus on Machine Learning is a strong plus.
• Extensive knowledge and practical experience in several of the following areas: machine vision (classical methods and deep learning) and information retrieval. Natural language processing is a plus.
• Demonstrated experience in building scalable AI/ML models and systems and delivering end-to-end solutions in a production environment.
• Experience programming in Python, C++, or related languages

Preferred qualifications

• Publications at top-tier peer-reviewed conferences or journals or a proven track record of industry innovation in creating novel solutions and advancing the state of the art.
• Experience with machine learning libraries and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with end-to-end software development and life cycle of machine learning solutions.
• Excellent verbal and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization

What’s in it for you

Generous financial reward for your effort

• Twice a year compensation reviews
• Generous equity package
• 5% employer match on pension

Time off and flexible working

• 25 days paid annual leave + bank holidays
• Ability to work from abroad for up to 6 weeks/year
• Competitive maternity + paternity leave
• Flexible hours and hybrid working
• Additional leave to support you when you need it, including sick pay, compassionate leave, or paid time-off to recharge after an intense work period

Support for your health and wellbeing

• Highest tier of private health coverage through Bupa
• Access to a virtual GP through Babylon
• Mental health and career coaching through Sanctus
• Free annual Headspace subscription

Additional perks

• L&D budget to use on Learnerbly (our learning platform)
• Cycle to Work scheme

The Mission:

As a Machine Learning Engineer, you will be responsible for building innovative web applications that deliver the power of Generative AI to our customers. You will work closely with designers, product managers and driving the technical designs and implementations.

Core Responsibilities:

We are looking for strong Machine Learning engineers across multiple levels to join our team and help us build innovative Generative AI solutions that deliver the power of Generative AI to our customers. You will be responsible for:

1. Define the roadmap for generation of various content types including text, image, audio and video enabling us to generate brand-affinitized, hyper-personalized, and safe content

2. Own the delivery of key business, product and technology initiatives across design, specification, development, testing, and launch.

3. Establish and implement processes for fine-tuning, testing, and operating the Generative AI models at significant scale.

4. Investigate, prototype and deliver innovative solutions

5. Collaborate with Product and Business Teams to identify new ways to improve our product and drive growth

6. Establish a data-driven development culture by driving the definition, tracking, and operationalizing of feature, product, and company-level metrics

Minimum Qualifications:

· Master’s or PhD degree in Computer Science or a related field

· 3+ years of prior experience designing, building and scaling systems for training, testing, and running Machine Learning models at scale

· Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects

· Hands-on development experience in Python, R, Rust, Java or C#.

· Ability to create self-contained, reusable, and testable modules

· Experience with building and evolving ML Training and Inferencing systems at significant scale.

Preferred Qualifications:

· Prior experience with AzureML, GCP Vertex, AWS Sagemaker or similar platforms

· Hands-on experience in deploying and tuning Generative AI models in cloud or on local system is a plus

· Experience working at a high-growth startup or tech company.

We are thrilled to expand our team and are actively seeking talented engineers who are passionate and motivated by our ambitious mission. We strive to create a collaborative environment where individuals can work on groundbreaking technology.

What we're looking for

We're looking for a skilled and motivated AI Research Engineer with deep knowledge in machine learning and NLP to join our team. You'll research and develop novel AI algorithms with large language models. We are looking for someone excited to try new ideas, read the latest papers and drive the model development from research to implementation.

Responsibilities

• Develop new research ideas and algorithms to improve our models

• Effectively manage and track model training experiments to maintain an organized record of results

• Work on our machine learning training codebase to allow for fast iterations and learnings

• Evaluate models and compare results to learn from each experiment

• Process large datasets with parallelization in mind

• Analyze datasets to find insights and track potential bugs

• Stay up-to-date with the latest research in NLP and large language models

• Deploy models to production and integrate with our backend

Experience

• Trained and shipped NLP models to production

• Strong coding skills in Python and knowledge machine learning frameworks (PyTorch, Jax, TensorFlow)

• Worked with large, complex datasets and analyzed data trends and patterns

• Deep knowledge of NLP models (GPT, BERT, T5, etc) and tasks

• Built data pipelines (for example with Airflow, Beam) with a cloud provider (AWS, GCP, Azure)

• Computer vision knowledge (diffusion models, CNN)

• 4+ years of working full-time

• Nice to have: Academic publications in the field of NLP/LLM

Role

As Founding AI Engineer, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed.

• Own the training and development of new customer-facing generative AI design models

• Build proprietary generative AI models

• Work directly with our CEO and founders

• Build our engineering organization

• Meet with customers to understand their problems and design solutions to address them

• Optimize applications for speed and scale

Qualifications

• 5+ years of relevant AI research or AI engineering experience.

• Experience with latest generative AI design models like DALL-E, Stable Diffusion,

  Midjourney.

• Have a track record of coming up with new ideas or improving upon existing ideas in AI,

  demonstrated by accomplishments such as first author publications or projects.

• Love to ship great products at lightning speed.

• Programming languages: Our current stack is Python and HuggingFace, and are looking

  to scale our system and architecture to the enterprise level.

• CS degree.

Nice to haves

• PhD or MS in CS or AI preferred.

• Early engineer at a hyper-growth startup.

• Experience at world class AI / engineering organizations.

• Experience with running generative AI models in production environments.

• Experience building data pipelines.

• NYC or Bay Area based.