We are seeking a highly skilled Senior NLP Research Scientist to join our team and lead the development and training of large language models for the healthcare space. The ideal candidate will have a strong background in natural language processing, machine learning, and deep learning, with experience in building and training large-scale language models, as well as pre-trained language models used for generative AI.

Responsibilities:

• Design and implement state-of-the-art NLP models for healthcare applications

• Train large language models on large-scale datasets

• Develop and implement model alignment algorithms including instruction tuning and RLHF

• Collaborate with cross-functional teams to integrate NLP models into healthcare applications

• Stay up-to-date with the latest research in NLP and machine learning

• Develop and fine-tune pre-trained language models for generative AI applications in healthcare

Requirements:

• PhD in Computer Science, Electrical Engineering, or related field

• 5+ years of experience in NLP and machine learning

• Strong programming skills in Python and experience with deep learning frameworks such as TensorFlow or PyTorch

• Experience with large-scale data processing and distributed computing

• Strong communication and collaboration skills

• Experience in healthcare or life sciences is a plus

• Experience with transformer based pre-trained language models including decoder-only architectures such as GPT and decoder-encoder architectures such as BERT

If you are passionate about NLP and want to make a difference in the healthcare industry, we encourage you to apply for this exciting opportunity.

Ideogram

Ideogram is a new generative AI startup looking for a dedicated Machine Learning Engineer to join the team.

Engineering Culture

We're a small and committed technical team that oversees engineering, research, design, product, and operation. Everyone on the team is willing to do whatever necessary to create a delightful product for our customers. We believe that a small dedicated team with a collaborative culture can move faster and build better and more coherent products than large hierarchical organizations.

As a member of our technical team, you’ll own projects end-to-end, directly engaging with our customers. From designing a machine learning system to developing the product and UX design, you will have a direct impact. At Ideogram, we provide mentorship and support to help our employees grow with the company and achieve their ambitious career goals.

About The Role

As a Machine Learning Engineer, you will build and deploy state of the art machine learning models at scale. You will work with a creative and ambitious team of engineers and researchers who are building the future of the creative economy with highly complex challenges.

What We're Looking For

• 5+ years of experience in developing machine learning models in JAX, PyTorch, and TensorFlow.

• Track record in machine learning innovation and familiarity with advanced machine learning methods (e.g., Transformer, VAE, Denoising Diffusion models) and experience in implementing them from scratch.

• End-to-end understanding of generative media applications and excitement for pushing the state-of-the-art in generative AI.

• Ability to debug machine learning models to iteratively improve model quality and performance.

• Familiarity with kubernetes and docker.

• (Optional) Experience in low-level machine learning optimization, e.g., writing CUDA kernel code.

Ideogram is committed to welcoming everyone, regardless of gender identity, orientation, or expression. Our mission is to remove exclusivity and barriers and encourage new thinking and perceptions, in a space of belonging. It is not about race, gender, or age, it is about the people.

Compensation range: 160k-250K CAD + Equity

About the Role

You will actively contribute to the development of AI models that are powering our innovative products. You will wear multiple hats and work on engineering, research, and everything in between. Your contributions will span model architectures, data curation, training and inference infrastructures, evaluation protocols, alignment and RLHF, and many other exciting topics at the cutting edge of AI. You will explore and exploit, creating new and perfecting existing methods.

You are expected to have a demonstrated track record of excellence in your field and the desire to learn and grow. While prior experience in large-scale AI is desirable, it’s not strictly required: many team members started out as physicists and mathematicians. You should be well familiar with the state of the art in AI, and passionate about conversational AI and its deployment.

About the Role

You will actively contribute to the development of AI models that are powering our innovative products. You will wear multiple hats and work on engineering, research, and everything in between. Your contributions will span model architectures, data curation, training and inference infrastructures, evaluation protocols, alignment and RLHF, and many other exciting topics at the cutting edge of AI. You will explore and exploit, creating new and perfecting existing methods.

You are expected to have a demonstrated track record of excellence in your field and the desire to learn and grow. While prior experience in large-scale AI is desirable, it’s not strictly required: many team members started out as physicists and mathematicians. You should be well familiar with the state of the art in AI, and passionate about conversational AI and its deployment.

Employee Pay Disclosures

At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. The pay range for this position in California, is estimated to fall in the base range of approximately $150,000 - $300,000. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range.

About the Role

At Inflection, the scale of our compute is critical to our mission of creating personal intelligence for everyone. We have several clusters in production currently, and are continually expanding our compute capacity. You’ll have the opportunity to work on the most powerful AI cluster in the world comprising 22K nVidia H-100 chips.

Inflection announces build of largest ML cluster in the world

As a Higher Performance Compute practitioner, you will be responsible for the smooth operation of these clusters on a day to day basis. You will be expected to add monitoring and telemetry to the clusters to preempt any issues that may arise, and on some occasions when issues do happen, you will be expected to put on your firefighting skills and resolve them. You will be monitoring jobs running on thousands of GPUs, or looking at workloads and their utilization. You will be partnering with other members of technical staff at Inflection to understand their needs and how to best achieve them.

Experience as a HPC practitioner and with schedulers such as SLURM and Kubernetes will be key for your success in this role. Knowledge of GPUs and their architectures as well as common failures is also important. Familiarity with LLMs and the current state and trends in NLP will also help. Finally, comfortably stepping into any problem with the HPC infrastructure and resolving it is essential for success in this role.

Minimum Requirements:

• Direct experience managing a multi-100-node+ Slurm cluster
• Direct experience with debugging massively parallel CPU/GPU jobs

Preferred experience:

• Managing ML-specific workloads on large GPU clusters on Slurm or Kubernetes

Employee Pay Disclosures

At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. The pay range for this position in California, is estimated to fall in the base range of approximately $150,000 - $300,000. This estimate can vary based on the factors described above, so the actual starting annual base salary may be above or below this range.

• Ph.D. in computer vision, machine learning, computer science, clinical machine learning or a related discipline, or equivalent practical experience (e.g., a Master’s degree plus 2 years of relevant industry experience)
• Experience developing models for diverse computer vision tasks (e.g. segmentation, recognition, classification, domain adaptation) including using modern deep learning frameworks (PyTorch, JAX, Keras, etc)
• Extensive hands-on experience working with biomedical imaging modalities
• Experience with modern representation learning approaches such as self-supervised learning, transfer learning, multi-modal modeling, few-shot learning, and more
• Strong programming skills in Python, including processing TB-scale image datasets using Linux/Bash
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference in the world

• Experience building infrastructure for clinical image dataset preprocessing
• Experience with real-world challenges of clinical data analysis, including working with clinical datasets such as EHR/PACS or clinical trial data and interactions with clinicians
• Demonstrated ability to write software in a team, through industry experience or substantial involvement with open source projects
• Some understanding of human physiology or disease biology (especially cancer, metabolism, or neurodegeneration)
• Publication record of meaningful contributions to high-quality work in relevant computer vision, clinical ML, or biomedical venues
• Familiarity with cloud computing services (e.g., AWS or GCP)
• Proficiency in C++/OpenCV/CUDA, or other compiled, statically-typed languages and related computer vision/graphics libraries

The Opportunity

Global drug development productivity is declining exponentially, with an overall failure to develop effective treatments for many increasingly prevalent complex diseases affecting millions of patients per year. We seek to tackle this by combining innovative machine learning techniques with pioneering technologies that measure multiple cellular aspects, aiming to drastically improve and accelerate how drugs are discovered and developed.

We are looking for highly motivated interns to join the data science & machine learning (DSML) team looking to work at the intersection of machine learning and life sciences for our Summer 2024 cohort.

You will partner directly with a DSML team mentor in developing and/or applying ML methods to process and analyze large scale datasets from multiple modalities over the course of the summer (11 weeks). The DSML diverse team that works across the company spanning imaging, omics, statistical genetics, small molecule discovery, clinical research, and research software engineering.

Example of areas & topics you will be working on:

• Computational Biology:
• Perform single cell transcriptomics data analysis, including cell type annotation and modeling of differentiation trajectories using RNA velocity;
• Use bioinformatic methods to perform downstream analysis in order to extract insights about disease mechanisms, such genes and pathways that are relevant to the therapeutic areas;
• Methods for Omics & Imaging data modalities:
• Develop, productionize, and deploy cutting-edge ML approaches to analyze and integrate large-scale multi-modal phenotypic datasets, including multi-omic; modalities (single-cell (sc) transcriptomics, sc-ATAC-seq), and imaging (e.g. brightfield, histopathology).
• Develop ML methods to process and analyze images from multiple microscopy modalities and integrate our in-vitro imaging data to extract insights about disease mechanisms.
• Research Engineering:
• Explore several recent papers on self-supervised learning for images and demonstrate whether they provide practical benefits when applied to insitro’s internal biological datasets, compared to our current algorithms;
• Help us integrate new large language models into our analysis tools to help our analysts get more out of our experimental data, faster.
• Statistical and Translational Genetics:
• Develop workflows to enable post-GWAS (Genome-Wide Association Scan) analysis of results, e.g. fine-mapping
• Translational genetics deep dives: enabling higher throughput annotation and exploration of candidate genes from our discovery efforts
• Pipelines to better derive and leverage metadata from sequenced cell lines and to incorporate this into image-based ML feature extraction
• Design of statistical methods to improve rare variant burden tests, and methods to improve power in longitudinal phenotypes
• Clinical Machine Learning
• Develop ML models for imputing disease-relevant phenotypes from high-content clinical imaging or time series data (e.g., histopathology, MRI/PET-CT, EEG, EKG)
• Develop ML methods for disentangling axes of variation in complex phenotypes
• Use LLMs to extract disease-relevant information from medical records
• Small Molecule Machine Learning:
• Build rich embedding models using DNA-Encode Library (DEL) data, and use these representations for downstream drug discovery tasks such as hit-discovery.
• Explore generative models of small molecules in various data modalities such as 2D and 3D representations for hit-to-lead drug discovery efforts.
• Develop new geometric deep learning methods to better characterize nuanced molecular properties and relationships.

What you will learn through this experience:

• In the course of the internship you will learn diverse machine learning techniques and rigorously analyze complex dataset and design metrics to ensure robustness of our methods.
• You can expect to develop and prototype solutions to enable ML based decisions in our automated workflows.
• You will work closely with machine learning engineers and scientists, biologists, chemists, microscopy experts, and automation engineers.
• You will be mentored by one of our senior researchers, who has significant experience in machine learning and computational biology.
• You will also attend our machine learning team meetings and will be exposed to a diverse set of novel technologies and machine learning concepts that tackle various biological questions.

In return, we will support you by:

• Placing a high degree of trust in your ideas and execution
• Bringing you up to speed in the domain of drug development
• Strive to provide a low-stress work environment
• Making ourselves available for collaboration
• Caring about you as a whole person - not a resource
• Being a well funded startup with conservative runway

About You

• Working towards a BS, MS, or Ph.D. in engineering, computational biology, systems biology, computer science, mathematics, statistics, life science, chemistry, physics, or a related field
• Proficiency in one or more general-purpose programming languages. We primarily use Python
• Interest in using and developing brand new statistical and machine learning methods inspired by real problems
• Curiosity about human physiology or disease biology
• Committed to writing high-quality, well-commented code and documentation
• Ability to communicate effectively and collaborate with people of diverse group of backgrounds and job functions
• Passion for making a difference in the world

Nice to Have

• First-hand experience with biological data, preferably using computational approaches
• Passion for learning how to work with diverse functional genomic assays (RNA/DNase/ATAC/ChIP-seq, etc)
• Interest in learning how to analyze single-cell RNA-seq data
• Solid understanding of computational chemistry, including virtual screening (classic QSAR modeling, structure based drug-discovery), library design, etc
• Demonstrated ability to use and develop cutting edge statistical and machine learning methods inspired by real problems
• Experience with Machine and Deep Learning frameworks (e.g., scikit-learn, PyTorch, etc.)
• Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)
• Experience in Linux environment, database languages (e.g., SQL, No-SQL) and version control practices and tools such as Git or Mercurial
• Publications of high-quality work in relevant computational biology, bioinformatics, systems biology, life sciences, or biomedical venues, including journals and conferences
• Passionate about solving problems, asking questions and learning independently
• Familiarity with the SciPy/PyData ecosystem (numpy, pandas, scipy, dask etc.)
• Familiarity with cloud computing services (AWS or GCP)
• Familiarity with statistical analysis software, e.g. R

• Ph.D. in computer vision, machine learning, computer science or a related discipline, or equivalent practical experience (e.g., a Master’s degree plus 2 years of relevant industry experience)
• Effective in team-based software design and development
• Demonstrated ability to use and develop cutting edge methods for analyzing imaging data
• Extensive hands on experience working with microscopy data or similar biomedical or biophysical imaging modalities
• Experience developing models for diverse computer vision tasks (e.g. segmentation, recognition, classification, domain adaptation) including using modern deep learning frameworks (PyTorch, TensorFlow, Keras, etc)
• Strong programming skills in Python, including processing TB-scale image datasets
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference in the world

• Demonstrated ability to write software in a team, industry experience or substantial involvement with open source projects.
• Experience modeling with video or imaging time-series datasets
• Experience building infrastructure for image preprocessing
• Experience with microscopy data acquisition
• Some understanding of image formation models (Fourier optics)
• Familiarity with cloud computing services (e.g., AWS or GCP)
• Experience with database languages (e.g., SQL)
• Publication record of meaningful contributions to high-quality work in relevant computer vision, clinical ML, or biomedical venues
• Proficiency in C++/OpenCV/CUDA, or other compiled, statically-typed languages and related computer vision/graphics libraries

• Lead and grow a team of outstanding machine learning imaging scientists
• Guide your team to develop and deploy ML to analyze data from diverse imaging modalities, ranging from fixed and live cell microscopy to histopathology to MRI
• Onboard and build on state of the art computer vision methods, while also bringing in an understanding of the unique needs of biomedical imaging modalities
• Lead yearly and quarterly planning, set impactful goals, and align with with cross-functional stakeholders
• Engineer robust, reusable platform components in partnership with the software engineering team
• Work with biologists and automation engineers to design experiments that generate datasets that are fit for purpose for machine learning, including ones generated explicitly for training ML models
• Work with the corporate development and strategy teams to acquire relevant external data sets
• Collaborate with colleagues working on complementary data modalities (‘omics, clinical annotations, etc) to help produce a holistic, multimodal view on human disease stat

• Ph.D. in machine learning, computer vision, computer science, or a related discipline, or equivalent practical experience
• 5+ years experience working in industry and managing projects and deliverables
• Experience and demonstrated ability to build and lead teams of engineers and scientists, including recruiting and mentoring team members
• Demonstrated ability to architect and build reusable code infrastructure and work with engineering teams
• Demonstrated ability to use and develop cutting edge computer vision methods inspired by real problems
• Demonstrated ability to work with and analyze medical imaging data (e.g., histopathology), cell imaging data, or ideally both
• Experience in modern representation learning topics such as self-supervised learning, transfer learning, multi-modal modeling, few-shot learning, robustness and interpretability, uncertainty estimation, and more
• Experience using modern deep learning frameworks (PyTorch, Jax, etc)
• Proficiency in Python
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for making a difference in the world

• Publication record in high profile venues in machine learning, computer vision, or life sciences
• High profile venues in machine learning, computer vision, or life sciences
• Familiarity with cloud computing services (e.g., AWS or GCP)
• Exposure to basic concepts in biology or medicine
• Proficiency in scientific engineering and modern engineering practice

The Opportunity

insitro’s approach to rethinking drug development applies innovative data science and machine learning, at scale, throughout the discovery process. As a Research Engineer, you will help implement, validate, and deploy our largest and most complex methods and models. We work on a variety of problem domains and datasets, including multi-petabyte collections of high-content biological imaging, genomics, and biomolecular structures. To support insitro’s work at this scale, our team is passionate about the craft of scientific software engineering, ensuring that our tools, infrastructure, and models are scalable, correct, maintainable, and robust. You will work closely with our data scientists, software engineers, biologists, and laboratory scientists to find opportunities and implement projects that will aid our drug discovery efforts. Typical projects might include onboarding methods from research papers, reducing the cost of training existing models, crafting a framework for benchmarking competing methods, or working alongside scientists to deploy methods at scale. While not required, some knowledge of biological or chemical data is valuable in understanding the unique requirements and applications of ML to biology and drug discovery.

About You

• Ph.D. in computer science, statistics, mathematics, physics, engineering, plus two years additional experience, or equivalent experience (for example, BS plus 7 years experience)
• Research experience with modern data science techniques; machine learning experience is required, but expertise in other techniques may also be helpful, such as Bayesian inference or probabilistic programming
• Fluency in one or more general-purpose programming languages (strong preference for experience in scientific Python)
• Experience working with teams throughout the full lifecycle of designing, implementing, deploying, and maintaining robust scientific software
• Strong desire to deliver work that aids in pioneering drug discovery!

Nice to Have

• Experience building, shipping, and benchmarking large-scale ML systems, foundation models, or large language models (LLMs)
• Experience with data modalities relevant to drug discovery, such as microscopy, genetics, or natural language, including patient records, and scientific literature.
• Experience working on ML experimentation tooling and platforms
• Experience working with high-performance computing resources, such as GPU clusters
• Past experience working on multi-functional teams
• Previous open-source contributions or publications demonstrating impact in relevant projects

• 401(k) plan with employer matching for contributions
• Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees), as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave
• Quarterly budget for books and online courses for self-development
• Support to occasionally attend professional conferences that are meaningful to your career growth and development
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast
• Access to free onsite fitness center
• Commuter benefits

The Opportunity

Insitro’s mission is to bring better drugs faster to the patients who can benefit most, through machine learning and data at scale. A key part of that mission is to rapidly identify safe and effective molecules that modulate novel targets that emerge from our biology discovery engine. Towards that goal, we have been building a cutting-edge, machine-learning-enabled capability to design and optimize small molecule therapeutics. Our work is enabled by proprietary experimental capabilities, including: generation of extensive binding, selectivity and affinity data via our second generation DNA-encoded library (DEL) platform; rapid synthesis to assay; ML-enabled measurement and analysis of high-content cellular phenotypes driven by small molecule perturbations; and the enablement of active learning via internal lab capabilities and extensive automation. In this role, you will collaborate with our world-class teams in drug discovery, software engineering, lab automation, and cell biology to build a unique approach for rapidly designing and optimizing small molecule therapeutics that have high efficacy, low toxicity and excellent pharmaceutical properties.

In this role, you will:

• Work collaborative with our Drug Discovery leaders on the strategy for deployment of advanced ML to accelerate and optimize small molecule drug discovery
• Lead and grow a team of outstanding machine learning scientists
• Guide your team to develop and deploy ML methods to analyze data from diverse small molecule data sets, including DEL binding data, pharmacological properties, and high-content functional readouts
• Onboard and develop ML-based molecular design methods, spanning from large data regimes (e.g., from DELs) to low-data regimes (few-shot or zero-shot), and including both predictive models and generative models
• Lead yearly and quarterly planning, set impactful goals, and align with cross-functional stakeholders
• Engineer robust, reusable platform components in partnership with the software engineering team
• Work with our chemistry and automation teams to design experiments that generate datasets that are fit for purpose for machine learning, including ones generated explicitly for training ML models
• Collaborate with the corporate development and strategy teams to assess potential external partners for molecular design collaboration and to acquire external data sets

You will be joining an exciting tech bio startup that has long-term stability due to significant funding, but that is still very much in formation. You will have ample opportunities for growth and impact. You will work closely with a diverse and talented team, learn a broad range of skills, and help shape insitro’s culture, strategic direction, and outcomes. Join us, and help make a difference to patients!

About You

• Ph.D. in computer science, chemistry, biochemistry, or a related discipline, or equivalent practical experience (e.g., a Masters degree plus 2 years in relevant industry experience)
• At least 5 years of industry experience in the field, including at least 2 in a line management or technical leadership role
• Peer reviewed publications in high-quality conferences or journals
• Demonstrated in-depth knowledge in the foundations and practice of modern machine learning, including deep learning, and their application to diverse molecular design tasks ● Considerable experience working with machine learning methods for small molecule chemistry across diverse tasks
• Demonstrated ability to lead a team of scientists and engineers to plan, execute and deliver a full machine learning solution for challenging, real-world problems: sourcing and qualifying training data; designing and implementing machine learning models; testing & benchmarking; shipping stable, robust, high-performance code.
• Extensive experience developing models using modern deep learning frameworks (PyTorch, TensorFlow, Keras, etc)
• Demonstrated ability in software engineering, including expertise in one or more general-purpose programming languages (such as Python, Java, Scala, C/C++, or Go) and experience with cloud computing (preferably AWS)
• Proven ability to mentor, coach, and lead junior scientists
• Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
• Passion for providing better medicine to patients in need

Nice to have

• Experience working on real world drug discovery campaigns
• Familiarity with non-ML methods for molecular design, such as traditional cheminformatics and molecular dynamics
• Exposure to ML methods in a low-data regime (few-shot or zero-shot learning)

The Opportunity

Machine learning lies at the core of insitro’s approach to rethinking drug development. Our team is responsible for the small molecule machine learning platform at insitro, and our responsibilities include design of high-throughput data generating experiments, design and execution of ML driven solutions for accelerating key problems in the drug discovery space, and creation of APIs and tooling for making the entire process reproducible and faster over time.

We are rapidly developing our small molecule hit-finding capabilities through cutting-edge machine learning technology. One of the key technologies we develop and leverage at insitro is DNA encoded libraries (DELs). Using DELs, we rapidly generate drug hits for validated targets coming out of our platform. Our combination of automated screening technology and machine learning enables us to extract promising hits from typically noisy DEL datasets and iterate far more rapidly than traditional high throughput screening approaches.

In this role, you will develop new models for molecule optimization utilizing data from multiple modalities, including DNA encoded libraries. To be effective, these models require powerful molecule representations that exploit relevant chemical principles and synthesize data from disparate sources. To achieve this, you’ll partner directly with chemists, machine learning scientists, hardware and software engineers, and clinicians to drive our drug discovery programs.

What you’ll do day to day:

• Deep dive into our DNA encoded libraries to define molecular models that incorporates the correct inductive biases to leverage the huge combinatorial datasets of DELs
• Collaborate cross-functionally with folks from our machine learning, automation, chemistry, and especially computational chemistry groups to develop new machine learning tools for hit discovery and lead optimization
• Directly shape the roadmap for our ChemML platform
• Shape our team’s culture with your ideas and experience
• All the normal ML stuff: document your method development, implement and share your methods in code, write and review design docs, talk to collaborators, and do code reviews
• Ultimately you’ll move the needle in a meaningful way for insitro and the field of medicine!

Examples of projects you will be working on:

• Design new model architectures that leverage knowledge about the chemical building blocks used to synthesize our DNA encoded libraries
• Leverage novel generative methods to generate new molecules in 2D and 3D space
• Better understand and develop machine learning methods for making out-of-distribution predictions for molecular datasets
• Collaborate with our software engineering teams to streamline dataset generation for model training
• Collaborate with our clinical scientists to deploy your models to accelerate a specific therapeutic area pipeline

In return, we will support you by:

• Placing a high degree of trust in your ideas and execution
• Bringing you up to speed on our DNA encoded library technology
• Making ourselves available for collaboration
• Caring about you as a whole person - not a resource
• Being a well funded startup with conservative runway

About you:

• You have 5+ years of experience as a machine learning scientist, with 2+ years of experience with chemistry datasets
• You’re eager to ship work that makes a difference to scientists and ultimately patients
• You feel comfortable reasoning about the tradeoffs between quality and speed when building in a startup environment
• You have experience with at least one high-end ML development environment such as Tensorflow or Pytorch
• You have experience with at least one cheminformatics toolkit such as OpenEye, RDKit, or Schrodinger
• You’ve demonstrated your ability to develop novel machine learning methods that go beyond putting together existing code, and to apply problem-solving skills to complex issues in the chemistry domain
• Bonus
• Experience with protein-ligand binding datasets
• Experience with DNA encoded library datasets
• Experience with our software stack: AWS, python, SQLAlchemy, PostgreSQL, Docker, workflow engines such as redun, pytorch

Compensation & Benefits at insitro:

Our target starting salary for successful US-based applicants for this role is $170,000 - $225,000. To determine starting pay, we consider multiple job-related factors including a candidate’s skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.

This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.

In addition, insitro also provides our employees:

• 401(k) plan with employer matching for contributions
• Excellent medical, dental, and vision coverage (insitro pays 100% of premiums for employees), as well as mental health and well-being support
• Open, flexible vacation policy
• Paid parental leave
• Quarterly budget for books and online courses for self-development
• Support to occasionally attend professional conferences that are meaningful to your career growth and development
• New hire stipend for home office setup
• Monthly cell phone & internet stipend
• Access to free onsite baristas and cafe with daily lunch and breakfast
• Access to free onsite fitness center
• Commuter benefits

We are seeking Staff and Principal level Machine Learning Engineers with extensive experience in Natural Language Processing (NLP). You will be at the forefront of building generative AI products that utilize Large Language Models (LLMs) to create next-generation AI characters.

Qualifications

• BA/BS degree or higher in Computer Science, Engineering, or a similar technical field.
• 6 years of experience with software development in one or more programming languages
• 4 years of experience with applying machine learning algorithms in natural language processing domains.
• 1+ years of experience training LLMs (6B parameters and larger) such as NeoX, LLaMA, PaLM, etc. is considered a big plus.
• Deep knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX.

Responsibilities

• Explore and experiment with cutting edge ML techniques for applied NLP.
• Develop and test production-grade scalable generative machine learning models.

In-office location: Vancouver, Canada.

Remote location: Canada.

We are seeking Staff and Principal level Machine Learning Engineers with extensive experience in Natural Language Processing (NLP). You will be at the forefront of building generative AI products that utilize Large Language Models (LLMs) to create next-generation AI characters.

Qualifications

• BA/BS degree or higher in Computer Science, Engineering, or a similar technical field.
• 6 years of experience with software development in one or more programming languages
• 4 years of experience with applying machine learning algorithms in natural language processing domains.
• 1+ years of experience training LLMs (6B parameters and larger) such as NeoX, LLaMA, PaLM, etc. is considered a big plus.
• Deep knowledge of machine learning frameworks such as PyTorch, TensorFlow, or JAX.

Responsibilities

• Explore and experiment with cutting edge ML techniques for applied NLP.
• Develop and test production-grade scalable generative machine learning models.

In-office location: Mountain View, CA, United States.

Remote location: United States.

The US base salary range for this full-time position is $220,000 - $350,000. In addition to base pay, total compensation includes equity and benefits. Within the range, individual pay is determined by work location, level, and additional factors, including competencies, experience, and business needs. The base pay range is subject to change and may be modified in the future.

Research Scientist, Machine Learning, London

Your impact

As a Research Scientist in machine learning (ML), you will play an exciting role in building greenfield machine learning based models and algorithms that will power our platform to transform the drug discovery world as we know it.

Working in a highly creative, fast-paced and interdisciplinary environment, you will be partnering with leading engineers and scientists to conceive, design, and develop cutting edge machine learning algorithms to unlock new modelling and predictive power which will be critical to the organisation’s success. You will draw upon your existing deep research experience whilst learning from those around you, to apply novel techniques and ideas to newly encountered computational biology and chemistry problems.

What you will do

• Contribute to our research directions in machine learning by using your extensive knowledge of the field to apply world-leading ML algorithms to drug discovery.
• Identify and create novel ML techniques and the required data to train.
• Develop the architectures and training algorithms of machine learning models.
• Analyse and tune experimental results to inform future experimental directions.
• Implement and scale training and inference engineering frameworks.
• Report and present research findings and developments clearly and efficiently, to both other ML scientists and scientists of different disciplines.
• Iterate collaboratively with scientists and domain experts, sharing your own domain experience.
• Suggest and engage in team collaborations to meet ambitious research goals.

Skills and qualifications

Essential

• PhD or equivalent practical experience in a technical field.
• A proven track record in machine learning using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation.
• Strong knowledge of linear algebra, calculus and statistics
• Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas
• A passion for applying ML research to real world problems

Nice to have

• PhD in machine learning or computer science.
• Relevant research experience to the position such as post doctoral roles, a proven track record of publications, or contributions to machine learning codebases.
• Scientific knowledge of biology, chemistry, or physics
• Experience working in a scientific environment across disciplines (particularly biology, chemistry, physics)
• Experience working with biological or chemical data and biological or chemistry software
• Experience working with real-world datasets
• Experience with ML on accelerators
• Experience in any of: large scale deep learning, generative models, graph neural networks, deep learning for drug discovery, deep learning for 3D graphics/robotics, real-world applied RL.

Responsibilities

• Conduct cutting-edge research in LLMs, multimodal models, and resource-constrained settings, contributing to the company's overall research agenda.
• Develop and implement novel algorithms, techniques, and models using state-of-the-art approaches such as fine-tuning methods, federated learning, and knowledge distillation.
• Collaborate with the research team, as well as external partners, to enhance our research capabilities and drive innovation.
• Publish research findings in top-tier conferences and journals such as NeurIPS, ICML, and ACL, and present at industry events to showcase our advancements and maintain our position as an industry leader.
• Provide technical guidance and mentorship to junior researchers and engineers, fostering a culture of collaboration and continuous learning.
• Stay up-to-date on industry trends, competitor activities, and emerging technologies to ensure our research remains relevant and cutting-edge.

Required Qualifications

• PhD in Computer Science, Artificial Intelligence, or a related field.
• 4+ years of experience in AI research, with a focus on LLMs and multimodal models.
• Strong track record of published research and conference presentations in relevant fields, particularly at top-tier conferences such as NeurIPS, ICML, and ACL.
• Proficient in Python, TensorFlow, PyTorch, and other relevant AI and machine learning frameworks.
• Experience with advanced techniques in fine-tuning, federated learning, and knowledge distillation for LLMs and multimodal models.
• Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Excellent communication and collaboration skills, with experience mentoring and guiding junior team members.

About the Job

This role works on our Machine Learning team and is responsible for developing and improving state of the art models to unlock the most effective work flows for students, teachers, and parents. This role will have the opportunity to work on both extremely high business value features and capabilities, as well as develop and execute research plans for green-grass work on the intersection of machine learning and education’s most exciting topics.

Things We Look For

• PhD in Computer Science or related field

• 5+ years of deep learning development in an academic or applied NLP setting

• Experience with conversational dialogue agents

• Interest in education and human computer and robot interaction

Benefits and Compensation

This position offers competitive compensation packages and benefits, including:

• Competitive salary + equity + benefits

• Unlimited PTO (Paid Time Off)

• Company holidays

• Health insurance

• Dental insurance

• Vision insurance

• Retirement accounts

• Flexible remote work

$130k-$250k + equity + benefits

Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Judie AI offers benefits.

We are not sponsoring visas at this time.

The Role

We are hiring a Machine Learning Engineer for Search Relevance. You will be responsible for ensuring that our system provides the highest quality search results in the industry for all our customers, demos and application areas. You will devise evaluation strategies, build evaluation sets, run benchmarks, ensure quality monitoring is in place, and set the agenda / prioritization for where to focus our quality iterations. You will be empowered to model & prototype solutions and will either get them implemented in production or work with one of our other ML engineers and Applied Scientists to make sure it gets implemented at the highest standard of quality. You have exceptional attention to detail, love finding the root cause problems for things. You understand the arguments for Data Centric ML and are excited by the latest developments in LLMs, pre-training, fine-tuning, instruction-tuning and in-context learning.

Who you are

• You love to learn and look for ways to learn at an accelerated pace
• You are compassionate and help others around you
• You can quickly hit the ground running, map out challenges and opportunities and develop a plan to improve things in the short and long term
• You have strong ownership of any task that you take on, driving it to success whether or not you've done it before
• You can cut through ambiguity and deliver amazing results even when there isn't a lot of guidance
• You are always looking for better ways of doing things, trying out new tools and processes
• You form meaningful relationships wherever you go: people respect and like you because you value them
• You seek continuous feedback from those around you and are willing to share feedback across all levels of the company

Requirements & Skills

• Experience with deep learning, LLMs, and Transformers
• Tech stack: PyTorch, Python, and Pandas
• Experience in search and recommendations is welcome but not required
• Preferred Masters in Computer Science, Data Science, Machine Learning, or related field

Benefits

• Competitive salary and equity.
• Platinum-level health, dental, and vision insurance for you and your family. We cover 99% of employee premiums and 95% of dependent premiums.
• Flexible Work - remote or in-person. We have a flexible work environment - work remotely from any U.S. timezone, or join us in-person at our San Francisco office.
• Unlimited PTO - take time when you need it to rest, relax, and recharge with unlimited PTO (minimum 4 weeks encouraged).
• Team events. Distributed work is awesome, but so is getting together in-person. Hang out with your colleagues at planned team events around the country.
• Brand new MacBook Pro (or PC if you prefer)

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Kailua Labs we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Kailua Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

The Role

We are hiring a staff machine learning engineer to build the next generation of personalized multimodal search. You’ll be joining as one of the earliest team members & will be critical to helping the team iterate and develop a product our customers love. This role is a great fit if you like moving quickly, can work across the stack when necessary and want a seat at the table making decisions about the future of the product & technology. The ideal candidate takes ownership over things and is excited to grow into a leadership position as the company and team grow in the future.

Who you are

• You love to learn and look for ways to learn at an accelerated pace
• You are compassionate and help others around you
• You can quickly hit the ground running, map out challenges and opportunities and develop a plan to improve things in the short and long term
• You have strong ownership of any task that you take on, driving it to success whether or not you've done it before
• You can cut through ambiguity and deliver amazing results even when there isn't a lot of guidance
• You are always looking for better ways of doing things, trying out new tools and processes
• You form meaningful relationships wherever you go: people respect and like you because you value them
• You seek continuous feedback from those around you and are willing to share feedback across all levels of the company

Requirements & Skills

• Experience with deep learning, LLMs, and Transformers
• Tech stack: PyTorch, TorchServe, Python, Pandas, NumPy, CUDA
• Experience in search and recommendations is welcome but not required

Benefits

• Competitive salary and equity.
• Platinum-level health, dental, and vision insurance for you and your family. We cover 99% of employee premiums and 95% of dependent premiums.
• Flexible Work - remote or in-person. We have a flexible work environment - work remotely from any U.S. timezone, or join us in-person at our San Francisco office.
• Unlimited PTO - take time when you need it to rest, relax, and recharge with unlimited PTO (minimum 4 weeks encouraged).
• Team events. Distributed work is awesome, but so is getting together in-person. Hang out with your colleagues at planned team events around the country.
• Brand new MacBook Pro (or PC if you prefer)

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. At Kailua Labs we are dedicated to building a diverse, inclusive and authentic workplace, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Kailua Labs provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

About Keeling Labs

About the Role

We're hiring for a skilled, tech-forward ML engineer to design and enhance our core training, experimentation, and deployment infrastructure. The ideal candidate will have built this from scratch in a previous role for an applied ML application solving an important problem.

What You’ll Be Responsible For:

• Design, build, and enhance core training infrastructure for our RL agents

• Closely collaborate with research scientists working on new agent designs

• Optimize large-scale training for cost, speed, and scale

• Develop CI/CD pipelines and ETL pipelines for a variety of applications

Requirements:

• 2+ years of industry experience building ML training infrastructure from scratch

• Experience architecting and implementing CI/CD pipelines

• Collaborative, results-oriented mindset, ability to work in a fast-paced environment, strong communication skills

• Frameworks: AWS (required), Kubernetes (required), Airflow (required), Docker (required), Spark (ideal), Pandas (required)

• Languages: Python (required), C/C++ (ideal)

• Willing and able to work in-person in Los Angeles

Job description:

We are seeking a highly experienced Lead Applied AI/ML Scientist with a specialization in deep learning and generative models to join our dynamic team. In this leadership role, you will guide the strategic direction of our AI modeling and implementation efforts, including the evaluation and fine-tuning of large language models. The ideal candidate has a robust understanding of the recent developments in reinforcement learning in a hindsight for fine-tuning (RLHF) and can adeptly apply this knowledge in a practical setting.

The ideal candidate is a self-motivated, entrepreneurial, and demonstrated team-player. You’ll be an early engineer and a key leader at a high growth startup, with a chance to play a significant role in building and bringing a new generative AI product to market.

Responsibilities:

• Lead the development, implementation, and continuous improvement of cutting-edge AI and machine learning models, with a focus on generative AI and large language models.
• Stay abreast of latest advancements in AI, machine learning, and deep learning research communities, and specifically, in fine-tuning methods such as RLHF, and adapt these advancements to our needs.
• Evaluate the performance of existing models using a variety of metrics, and recommend improvements as necessary.
• Leverage our rich datasets to fine-tune models and maximize their effectiveness.
• Collaborate closely with other teams within the company to understand their needs and develop AI models that support their objectives.
• Mentor and guide junior team members in the development and implementation of AI models.
• Present complex concepts and the results of research projects effectively to both technical and non-technical audiences.
• Lead research collaborations and partnerships with external researchers and institutions.

Required Qualifications:

• PhD in Computer Science, Machine Learning, AI, or a related field, or equivalent experience.
• Minimum of 10 years of experience in AI research with a strong focus on deep learning, generative models, and large language models.
• Extensive experience with the latest advancements in reinforcement learning for fine-tuning (RLHF).
• Proficient in machine learning frameworks such as TensorFlow, PyTorch, or others.
• Demonstrated ability to lead complex projects and guide junior team members.
• Excellent communication skills, with the ability to explain complex technical concepts to a non-technical audience.
• Published work in top-tier AI or machine learning conferences or journals is a plus.
• Strong problem-solving skills, and the ability to think critically and creatively.
• Onsite in Venice CA (for now - may extend to remote in the future)

Preferred Qualifications:

• Practical experience deploying LLMs into production
• Familiarity with open source frameworks like Langchain
• Knowledge of enterprise security best practices
• Experience with Enterprise SaaS software

What We Offer:

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Unlimited vacation and paid time off policies
• A flexible and dynamic work environment with opportunities for occasional remote work
• The opportunity to work alongside a talented team of engineers and innovators
• A chance to be part of a groundbreaking company shaping the future of generative AI

Company Culture:

• Start-up and entrepreneurial mindset: High-energy, passionate, and willing to put in a bit of extra energy to ensure we succeed, but mindful of work-life balance, protecting weekends, and accommodating personal obligations. Full belief in the multi-billion dollar market opportunity in front of us.
• Strong ownership culture: Complete ownership of core areas of responsibility, but also welcoming ideas and contributions from everyone. Everyone acts like product owners and contributes where they can provide value.
• Fast-paced and action-oriented: Focus on high velocity, minimal processes, and utilizing existing solutions to maximize product development and minimize maintenance overhead. Focused on outcomes over hours. We work smarter, not harder.
• Empathy, open-mindedness, and constructive feedback: Respect diverse working styles, encourage data-informed decisions, and build understanding and trust through direct conflict resolution
• Reflective thinking and effectiveness: Balance thoughtful planning and discipline with action, prioritize finding solutions that meet customer needs over being right
• Collaboration and support: Foster an environment where employees can work together, rely on each other, and support one another through challenges

If you are a passionate and talented AI researcher looking to make a meaningful impact in the generative AI space applied into end-user products, we would love to hear from you. Apply now and join our team of visionaries in creating the next unicorn company in the AI industry.

Job description:

We are seeking a highly experienced Senior Machine Learning (ML) Engineer with a specialization in deep learning and generative models to join our dynamic team. In this senior role, you will strongly influence the strategic direction of our AI modeling and implementation efforts, including the evaluation and fine-tuning of large language models. The ideal candidate has a robust understanding of the recent developments in reinforcement learning in a hindsight for fine-tuning (RLHF) and can adeptly apply this knowledge in a practical setting.

The ideal candidate is a self-motivated, entrepreneurial, and demonstrated team-player. You’ll be an early engineer and a key leader at a high growth startup, with a chance to play a significant role in building and bringing a new generative AI product to market.

Responsibilities:

• Lead the development, implementation, and continuous improvement of cutting-edge AI and machine learning models, with a focus on generative AI and large language models.
• Stay abreast of latest advancements in AI, machine learning, and deep learning research communities, and specifically, in fine-tuning methods such as RLHF, and adapt these advancements to our needs.
• Evaluate the performance of existing models using a variety of metrics, and recommend improvements as necessary.
• Leverage our rich datasets to fine-tune models and maximize their effectiveness.
• Collaborate closely with other teams within the company to understand their needs and develop AI models that support their objectives.
• Mentor and guide junior team members in the development and implementation of AI models.
• Present complex concepts and the results of research projects effectively to both technical and non-technical audiences.
• Lead research collaborations and partnerships with external researchers and institutions.

Required Qualifications:

• MS in Artificial Intelligence, Computer Science, Machine Learning, or a related field.
• Minimum of 5 years of experience in applied AI research with a strong focus on deep learning, generative models, and large language models.
• Extensive experience with the latest advancements in reinforcement learning for fine-tuning (RLHF).
• Proficient in machine learning frameworks such as TensorFlow, PyTorch, or others.
• Demonstrated ability to lead complex projects and guide junior team members.
• Excellent communication skills, with the ability to explain complex technical concepts to a non-technical audience.
• Published work in top-tier AI or machine learning conferences or journals is a plus.
• Strong problem-solving skills, and the ability to think critically and creatively.
• Onsite in Venice CA (for now - may extend to remote in the future)

Preferred Qualifications:

• Practical experience deploying LLMs into production
• Familiarity with open source frameworks like Langchain
• Knowledge of enterprise security best practices
• Experience with Enterprise SaaS software

What We Offer:

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Unlimited vacation and paid time off policies
• A flexible and dynamic work environment with opportunities for occasional remote work
• The opportunity to work alongside a talented team of engineers and innovators
• A chance to be part of a groundbreaking company shaping the future of generative AI

Company Culture:

• Start-up and entrepreneurial mindset: High-energy, passionate, and willing to put in a bit of extra energy to ensure we succeed, but mindful of work-life balance, protecting weekends, and accommodating personal obligations. Full belief in the multi-billion dollar market opportunity in front of us.
• Strong ownership culture: Complete ownership of core areas of responsibility, but also welcoming ideas and contributions from everyone. Everyone acts like product owners and contributes where they can provide value.
• Fast-paced and action-oriented: Focus on high velocity, minimal processes, and utilizing existing solutions to maximize product development and minimize maintenance overhead. Focused on outcomes over hours. We work smarter, not harder.
• Empathy, open-mindedness, and constructive feedback: Respect diverse working styles, encourage data-informed decisions, and build understanding and trust through direct conflict resolution
• Reflective thinking and effectiveness: Balance thoughtful planning and discipline with action, prioritize finding solutions that meet customer needs over being right
• Collaboration and support: Foster an environment where employees can work together, rely on each other, and support one another through challenges

If you are a passionate and talented AI researcher looking to make a meaningful impact in the generative AI space applied into end-user products, we would love to hear from you. Apply now and join our team of visionaries in creating the next unicorn company in the AI industry.

As a Prompt Engineer, you will be responsible for developing and refining text prompts that are used to train and control large language models. You will work closely with product, engineering, and data science to ensure that our prompts are accurate, engaging, and relevant. The ideal candidate is a self-motivated, entrepreneurial, and demonstrated team-player. You’ll be an early member at a high growth startup, with a chance to play a significant role in building and bringing a new generative AI product to market.

Responsibilities:

• Develop and refine text prompts for a variety of tasks, including generating text, translating languages, writing different kinds of creative content, and answering questions in an informative way.
• Work with product, engineering, and data science teams to gather requirements and design prompts that meet the needs of our users.
• Test and evaluate the performance of prompts to ensure that they are producing the desired results.
• Document and share best practices for prompt engineering with the team.
• Stay up-to-date on the latest research and trends in prompt engineering.
• Work with large enterprise customers on their prompting strategies.

Qualifications:

• As this is a newly developing field, please include a submission of a specific prompt engineering project on LLMs you’ve worked on. Ideally this project should show off a complex and clever prompting architecture or a systematic evaluation of an LLM’s behavior.
• Bachelor's degree in computer science, linguistics, or a related field.
• Strong understanding of the architecture and operation of large language models.
• Excellent communication and documentation skills.
• Ability to work independently and as part of a team.
• Passion for making powerful technology safe and societally beneficial.
• Demonstrated ability to work independently and ramp up quickly with minimal guidance
• Excellent problem-solving skills and a strong desire to learn and grow
• Strong communication and collaboration skills, with the ability to work effectively in a dynamic team environment
• Onsite in Venice CA (for now - may extend to remote in the future)

What We Offer:

• Competitive salary and equity package
• Comprehensive health, dental, and vision insurance
• Unlimited vacation and paid time off policies
• A flexible and dynamic work environment with opportunities for occasional remote work
• The opportunity to work alongside a talented team of engineers and innovators
• A chance to be part of a groundbreaking company shaping the future of generative AI

Company Culture:

• Start-up and entrepreneurial mindset: High-energy, passionate, and willing to put in a bit of extra energy to ensure we succeed, but mindful of work-life balance, protecting weekends, and accommodating personal obligations. Full belief in the multi-billion dollar market opportunity in front of us.
• Strong ownership culture: Complete ownership of core areas of responsibility, but also welcoming ideas and contributions from everyone. Everyone acts like product owners and contributes where they can provide value.
• Fast-paced and action-oriented: Focus on high velocity, minimal processes, and utilizing existing solutions to maximize product development and minimize maintenance overhead. Focused on outcomes over hours. We work smarter, not harder.
• Empathy, open-mindedness, and constructive feedback: Respect diverse working styles, encourage data-informed decisions, and build understanding and trust through direct conflict resolution
• Reflective thinking and effectiveness: Balance thoughtful planning and discipline with action, prioritize finding solutions that meet customer needs over being right
• Collaboration and support: Foster an environment where employees can work together, rely on each other, and support one another through challenges

If you are a passionate and talented engineer looking to make a meaningful impact in the generative AI space, we would love to hear from you. Apply now and join our team of visionaries in creating the next unicorn company in the AI industry.

The brilliant minds in R&D take our products to the next level using groundbreaking Machine Learning, Computer Graphics and AI features. Our state-of-the-art photo and video tools are based in computer vision, machine learning, rendering, deep learning and computational photography. To read more about our team’s work, read our tech blog.

We lead the research of next generation algorithms in the visual, auditory, and textual domains. A large part of our work is understanding how we can best engage with our customers and help them tap into their creativity. We deal with many diverse problem domains and aim to bring them to production in an efficient manner on top of both backend and edge systems.

What you will be doing

As research engineering backend team lead at Lightricks you will lead a small team of excellent engineers engaging in tasks ranging from building our backend ML platform to creating streamlined processes to bring functional research code to production grade systems.

On top of an excellent high level tech understanding, this role requires a combination of team player, good planning and execution skills, great communication skills, people management experience and high motivation for facing exciting challenges.

As part of being the manager of a growing team and a growing backend product, we are also looking for someone who can work hands on from time to time and escort the team bottom up when needed.

Your skills and experience

• 5+ years of experience working on backend systems.
• 2+ years of engineering management experience.
• Experience in system and API Design.
• Strong organizational and project management skills.
• Excellent communication and collaboration skills.
• Highly independent, accountable and a team player.
• Experience with Python/Golang/Java or an OO language.
• Experience developing a cloud-based system (AWS or GCP).
• Experience with Docker and Kubernetes is a plus.
• Experience working with ML and large compute systems is a plus.
• Experience with databases, preferably both SQL and NoSQL is a plus.

Benefits

• Stock Options.
• Private Medical Insurance. (Optical & Dental cover) including your loved ones.
• Life Assurance
• £3,000 Annual Lunch allowance.
• Free on-site catered lunches.
• £500p/a Well-being allowance.
• Free Coffee, Breakfast & snacks.
• £250p/a Professional development allowance.
• Pension Contributions (7%).
• Holiday (25 days).
• Seasonal & Anniversary Vouchers.
• Hybrid & Flexible working.
• Cool office space in central London.
• Volunteering Opportunities.
• Frequent social activities - away-days, happy hours, team building, yoga, creative workshops.

#LI-HYBRID

Overview:

We are seeking a talented and highly motivated Machine Learning Scientist to join our team and contribute to the development and deployment of cutting-edge machine learning models and algorithms. The successful candidate will work closely with cross-functional teams to solve complex business problems, improve existing systems, and push the boundaries of what is possible with machine learning.

In this role, you will:

As part of the Machine Learning team, you will have the opportunity to reimagine and build the next-generation personalization that enables brands and retailers to understand the cognitive attributes of customers online and the 'why' behind 'what they do' in their journey by pushing the boundaries of our ML systems and algorithms.

• Using proven techniques in computer vision and NLP to solve business challenges in the domain of deep product attribution, item setup and demand forecasting.
• Conduct research on the latest machine learning techniques, tools, and frameworks to identify and recommend potential improvements to existing models and systems.
• Design and perform experiments to validate and refine model performance, using both quantitative and qualitative methods.
• Assist in the development of production-ready code and integrate machine learning models into existing systems and workflows.
• Define the training-data roadmap for various ML tasks.
• Continuously monitor and analyze model performance in production, identifying opportunities for improvement and optimization.
• Maintain up-to-date knowledge of industry best practices, trends, and advancements in the field of machine learning.
• Collaborate with internal stakeholders for various org initiatives.
• Facilitate customer POCs and attend to escalations.

What we consider critical for this role:

• 8-12+ years of experience in building large scale machine learning solutions.
• Expertise in Python and PyTorch.
• Experience with Large Language/Multi-Modal Models.
• Experience with ML frameworks & platforms like Weights & Biases, PyTorch Lightning and HuggingFace.
• Experience in data wrangling and preprocessing techniques.
• Strong problem-solving, critical thinking, and analytical skills.
• Familiarity with cloud platforms like Azure.
• Familiarity with distributed systems.
• Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.

Compensation:

Compensation is competitive and will be determined based on a combination of experience, seniority, internal, external equity and location. For some context: this position in the US would pay between $160,000-$175,000 USD per year, depending on experience and seniority. In other regions, compensation will be adjusted for local currency and local market rates. Lily AI compensation policy is calculated with a focus on equity and where employees can thrive.

Overview:

We are looking for a skilled Machine Learning Engineer to join our team and help design, develop, and deploy advanced machine learning models and solutions for a variety of business problems. The successful candidate will collaborate with data scientists, software developers, and product managers to transform experimental models into production-ready systems, ensuring scalability, efficiency, and robustness.

In this role, you will:

As part of the Machine Learning team, you will have the opportunity to reimagine and build the next-generation personalization that enables brands and retailers to understand the cognitive attributes of customers online and the 'why' behind 'what they do' in their journey by pushing the boundaries of our ML systems and algorithms.

• Own the data, training and serving pipelines of Lily’s ML solutions from an engineering standpoint.
• Productionize ML based solutions as developed by our ML Scientists.
• Optimize and fine-tune machine learning models and algorithms using appropriate programming languages, libraries, and frameworks.
• Design and build ML serving pipelines with stringent SLAs.
• Continuously monitor and evaluate the performance of machine learning models in production, identifying areas for improvement and optimization.
• Adhere to software engineering best practices while maintaining our tech stack.
• Troubleshoot and resolve issues related to system integration, model performance, and data quality.
• Facilitate customer POCs and attend to escalations

What we consider critical for this role:

• Proficiency in Python, Pytorch and SciPy.
• Expertise in real-time serving and optimization tools for deep learning, e.g. Triton, TensorRT, PyTorch JIT, TorchScript, ONNX.
• Expertise in developing solutions on cloud platforms like AWS and Azure.
• Expertise in developing and maintaining efficient, scalable, and robust machine learning systems, integrating models into existing software systems and applications.
• Expertise in distributed systems concepts.
• Familiarity with Large Language/Multi-Modal Models.
• Strong understanding of machine learning concepts, techniques, and algorithms, with experience in applying these methods to real-world problems.
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Compensation:

Compensation is competitive and will be determined based on a combination of experience, seniority, internal, external equity and location. For some context: this position in the US would pay between $135,000-$180,000 USD per year, depending on experience and seniority. In other regions, compensation will be adjusted for local currency and local market rates. Lily AI compensation policy is calculated with a focus on equity and where employees can thrive.

Overview:

We are seeking a talented and highly motivated Machine Learning Scientist to join our team and contribute to the development and deployment of cutting-edge machine learning models and algorithms. The successful candidate will work closely with cross-functional teams to solve complex business problems, improve existing systems, and push the boundaries of what is possible with machine learning.

In this role, you will:

As part of the Machine Learning team, you will have the opportunity to reimagine and build the next-generation personalization that enables brands and retailers to understand the cognitive attributes of customers online and the 'why' behind 'what they do' in their journey by pushing the boundaries of our ML systems and algorithms.

• Using proven techniques in computer vision and NLP to solve business challenges in the domain of deep product attribution, item setup and demand forecasting.
• Conduct research on the latest machine learning techniques, tools, and frameworks to identify and recommend potential improvements to existing models and systems.
• Design and perform experiments to validate and refine model performance, using both quantitative and qualitative methods.
• Assist in the development of production-ready code and integrate machine learning models into existing systems and workflows.
• Define the training-data roadmap for various ML tasks.
• Continuously monitor and analyze model performance in production, identifying opportunities for improvement and optimization.
• Maintain up-to-date knowledge of industry best practices, trends, and advancements in the field of machine learning.
• Collaborate with internal stakeholders for various org initiatives.
• Facilitate customer POCs and attend to escalations.

What we consider critical for this role:

• 8-12+ years of experience in building large scale machine learning solutions.
• Expertise in Python and PyTorch.
• Experience with Large Language/Multi-Modal Models.
• Experience with ML frameworks & platforms like Weights & Biases, PyTorch Lightning and HuggingFace.
• Experience in data wrangling and preprocessing techniques.
• Strong problem-solving, critical thinking, and analytical skills.
• Familiarity with cloud platforms like Azure.
• Familiarity with distributed systems.
• Master's or Ph.D. in Computer Science, Data Science, Artificial Intelligence, or a related field.

Compensation:

Compensation is competitive and will be determined based on a combination of experience, seniority, internal, external equity and location. For some context: this position in the US would pay between $160,000-$175,000 USD per year, depending on experience and seniority. In other regions, compensation will be adjusted for local currency and local market rates. Lily AI compensation policy is calculated with a focus on equity and where employees can thrive.

LivePerson (NASDAQ: LPSN) is a global leader in trustworthy and equal AI for business. Hundreds of the world’s leading brands — including HSBC, Chipotle, and Virgin Media — use our Conversational Cloud platform to engage with millions of consumers safely and responsibly. We power a billion conversational interactions every month, providing a uniquely rich data set and safety tools to unlock the power of Generative AI and Large Language Models for better business outcomes.

At LivePerson, we foster an inclusive workplace culture that encourages meaningful connection, collaboration, and innovation. Every mind is invited to ask questions and actively seek new ways to achieve success and reach their full potential. We operate as one with a growth mindset. This means spotting opportunities, solving ambiguities and seeking effective solutions to challenges that make things better.

Overview

Our goal is to deliver the next-generation of Conversational AI (CAI), including the latest in Generative AI/Foundation Model technology. Towards this, we are building a multidisciplinary team of engineers and scientists to create a platform that can provide elegant conversational experiences at scale. We are looking for a CAI Engineer II to pursue, and implement exceptional conversational experiences.

You will

• Deliver state-of-the-art Conversational AI products at a global scale to tens of millions of consumers.
• Bridge the gap between (in house and external) generative AI capabilities and applications that use them to automate conversations at scale.
• Extend the latest foundation model capabilities to take action and solve real customer problems.
• Implement and deliver production-level ML-focused code
• Identify and rapidly prototype supporting technologies to showcase conversational elegance
• Develop authorship tooling for building and maintaining dialogue management products at scale

You have

• B.S. in a quantitative or computational field such as Computer Science, Artificial Intelligence, or equivalent experience
• 2 years of industry/academic experience with AI systems
• Experience delivering production software
• Proficient in Python
• Experience with Natural Language Understanding and/or Conversational AI techniques
• Experience with communicating insights and presenting concepts to diverse audiences.
• Team player mindset and ability to work in an interdisciplinary team.

Preferred qualifications:

• Experience designing conversational experiences for an end-user
• Experience conducting usability studies and focus groups
• Experience deploying Machine Learning models into production

Benefits:

• Health: medical, dental, and vision

• Time away: vacation and holidays

• Development: Native AI learning and Fast track growth opportunities

• Equal opportunity employer

Why you'll love working here:

LivePerson is a hub for the ever-curious and proactive, offering a flexible work-life balance tailored to individual needs. With offices and WeWork locations worldwide, our flexible work policy provides our teams the freedom to work from their preferred environment. We're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace.

Belonging at LivePerson:

We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

We are committed to the accessibility needs of applicants and employees. We provide reasonable accommodations to job applicants with physical or mental disabilities. Applicants with a disability who require reasonable accommodation for any part of the application or hiring process should inform their recruiting contact upon initial connection.

LivePerson (NASDAQ: LPSN) is a global leader in trustworthy and equal AI for business. Hundreds of the world’s leading brands — including HSBC, Chipotle, and Virgin Media — use our Conversational Cloud platform to engage with millions of consumers safely and responsibly. We power a billion conversational interactions every month, providing a uniquely rich data set and safety tools to unlock the power of Generative AI and Large Language Models for better business outcomes.

At LivePerson, we foster an inclusive workplace culture that encourages meaningful connection, collaboration, and innovation. Every mind is invited to ask questions and actively seek new ways to achieve success and reach their full potential. We operate as one with a growth mindset. This means spotting opportunities, solving ambiguities and seeking effective solutions to challenges that make things better.

Overview

Our goal is to deliver the next-generation of Conversational AI (CAI), including the latest in Generative AI/Foundation Model technology. Towards this, we are building a multidisciplinary team of engineers and scientists to create a platform that can provide elegant conversational experiences at scale. We are looking for a Conversational AI Engineer II to pursue, and implement exceptional conversational experiences.

You will:

• Deliver state-of-the-art Conversational AI products at a global scale to tens of millions of consumers.
• Bridge the gap between (in house and external) generative AI capabilities and applications that use them to automate conversations at scale.
• Extend the latest foundation model capabilities to take action and solve real customer problems.
• Implement and deliver production-level ML-focused code
• Identify and rapidly prototype supporting technologies to showcase conversational elegance
• Develop authorship tooling for building and maintaining dialogue management products at scale

You have:

• B.S. in a quantitative or computational field such as Computer Science, Artificial Intelligence, or equivalent experience
• 3+ years of industry/academic experience with AI systems
• Experience delivering production software
• Proficient in Python
• Experience with Natural Language Understanding and/or Conversational AI techniques
• Experience with communicating insights and presenting concepts to diverse audiences.
• Team player mindset and ability to work in an interdisciplinary team.

Preferred Qualifications:

• Experience designing conversational experiences for an end-user
• Experience conducting usability studies and focus groups
• Experience deploying Machine Learning models into production

Benefits:

• Health: medical, dental, and vision

• Time away: 28 vacation days

• Development: Native AI learning

• Additional: Food Vouchers.

Why you'll love working here:

LivePerson is a hub for the ever-curious and proactive, offering a flexible work-life balance tailored to individual needs. With offices and WeWork locations worldwide, our flexible work policy provides our teams the freedom to work from their preferred environment. We're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace.

Belonging at LivePerson:

We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

We are committed to the accessibility needs of applicants and employees. We provide reasonable accommodations to job applicants with physical or mental disabilities. Applicants with a disability who require reasonable accommodation for any part of the application or hiring process should inform their recruiting contact upon initial connection.

LivePerson (NASDAQ: LPSN) is a global leader in trustworthy and equal AI for business. Hundreds of the world’s leading brands — including HSBC, Chipotle, and Virgin Media — use our Conversational Cloud platform to engage with millions of consumers safely and responsibly. We power a billion conversational interactions every month, providing a uniquely rich data set and safety tools to unlock the power of Generative AI and Large Language Models for better business outcomes.

At LivePerson, we foster an inclusive workplace culture that encourages meaningful connection, collaboration, and innovation. Every mind is invited to ask questions and actively seek new ways to achieve success and reach their full potential. We operate as one with a growth mindset. This means spotting opportunities, solving ambiguities and seeking effective solutions to challenges that make things better.

Overview

Our goal is to deliver the next-generation of Conversational AI (CAI), including the latest in Generative AI/Foundation Model technology. Towards this, we are building a multidisciplinary team of engineers and scientists to create a platform that can provide elegant conversational experiences at scale. We are looking for a Conversational AI Engineer II to pursue, and implement exceptional conversational experiences.

You will:

• Deliver state-of-the-art Conversational AI products at a global scale to tens of millions of consumers.
• Bridge the gap between (in house and external) generative AI capabilities and applications that use them to automate conversations at scale.
• Extend the latest foundation model capabilities to take action and solve real customer problems.
• Implement and deliver production-level ML-focused code
• Identify and rapidly prototype supporting technologies to showcase conversational elegance
• Develop authorship tooling for building and maintaining dialogue management products at scale

You have:

• B.S. in a quantitative or computational field such as Computer Science, Artificial Intelligence, or equivalent experience
• 3+ years of industry/academic experience with AI systems
• Experience delivering production software
• Proficient in Python
• Experience with Natural Language Understanding and/or Conversational AI techniques
• Experience with communicating insights and presenting concepts to diverse audiences.
• Team player mindset and ability to work in an interdisciplinary team.

Preferred Qualifications:

• Experience designing conversational experiences for an end-user
• Experience conducting usability studies and focus groups
• Experience deploying Machine Learning models into production

Benefits:

• Health: medical, dental, and vision

• Time away: vacation and holidays

• Development: Native AI learning and Fast track growth opportunities

• Equal opportunity employer

Why you'll love working here:

LivePerson is a hub for the ever-curious and proactive, offering a flexible work-life balance tailored to individual needs. With offices and WeWork locations worldwide, our flexible work policy provides our teams the freedom to work from their preferred environment. We're very proud to have earned recognition from Fast Company, Newsweek, and BuiltIn for being a top innovative, beloved, and remote-friendly workplace.

Belonging at LivePerson:

We are proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants with criminal histories, consistent with applicable federal, state, and local law.

We are committed to the accessibility needs of applicants and employees. We provide reasonable accommodations to job applicants with physical or mental disabilities. Applicants with a disability who require reasonable accommodation for any part of the application or hiring process should inform their recruiting contact upon initial connection.

Startup Mindset

• Value velocity and execution.
• Communicate clearly.
• Focus on building what will matter to users and the product.
• Be resourceful at finding creative ways to overcome challenges.

Experience

• 5 years of academic or industry research experience in NeRF or related fields.
• Strong first principles understanding of Machine Learning.
• Proficiency in Python and PyTorch. CUDA is a plus, but not required.
• A strong foundation in 3D graphics is a plus, but not required.
• If you have worked on traditional 3D reconstruction (SfM) that's a plus.

Benefits

• Equity grant to reflect the incredible value you will bring to Luma, with annual refreshes.
• Excellent salary and benefits.
• Full health, dental, and vision coverage.
• Latest and greatest gear.
• Stipends towards wellness, house cleaner, and phone/internet.
• Unlimited paid time off with 12 days minimum.
• Unlimited sick days.

Why Join Luma?

• In any role here, you will work with people experts in their field, and learn a *lot*
• We build. We ship. Your work will matter to people.
• We are building a very widely usable product, and you’ll get to work on equally wide variety of challenging problems.
• We have fantastic traction from early customers, whom you’ll get to work directly with.
• We have backing of some of the best VCs in Silicon Valley, and Angels from across the industry.

Startup Mindset

• Value velocity and execution.
• Communicate clearly.
• Focus on building what will matter to users and the product.
• Be resourceful at finding creative ways to overcome challenges.

Experience

• 4+ years of academic or industry research experience with training generative models, especially GANs or diffusion models.
• Experience with large-scale distributed training and/or data collection is a plus.
• Strong first principles understanding of Machine Learning.
• A foundation in 3D graphics is a plus, but not required.
• Proficiency in Python and PyTorch.
• Proficiency in handling and processing large datasets.

Benefits

• Equity grant to reflect the incredible value you will bring to Luma, with annual refreshes.
• Excellent salary and benefits.
• Full health, dental, and vision coverage.
• Latest and greatest gear.
• Stipends towards wellness, house cleaner, and phone/internet.
• Unlimited paid time off with 12 days minimum.
• Unlimited sick days.

Why Join Luma?

• In any role here, you will work with people experts in their field, and learn a *lot*
• We build. We ship. Your work will matter to people.
• We are building a very widely usable product, and you’ll get to work on equally wide variety of challenging problems.
• We have fantastic traction from early customers, whom you’ll get to work directly with.
• We have backing of some of the best VCs in Silicon Valley, and Angels from across the industry.

We are seeking an ML Engineer to join our AI focused healthcare startup. Our team has deployed models that check for anomalies in medical claims, predict the trajectory of care of a particular patient and the next likely treatment and even “read and understand” medical record documents using state-of-the-art NLP and computer vision techniques to assist clinicians. There are many more such problems to be solved. So if you are looking for a place where you can apply your expertise in AI/ML to solve real problems and make a difference in an industry that impacts millions of lives while accelerating your career, you’ll love Machinify. We are seeking a Sr Machine Learning Scientist to join our team.

What you’ll do:

• Advance Machinify’s capabilities to model and understand medical decisions which will power a range of products in the claims processing space.

• Make thoughtful decisions around which methods/algorithms are likely to work well in solving the business problem at hand

• Consider the quality of the available input data and build robust systems that will work well in the presence of noise/errors

• Measure the model output in practical real-world settings and iterate your approach

• Learn about the healthcare industry and become an expert over time

What You Bring:

• You enjoy solving real-world business problems by developing, from scratch, ML models and deploying them in production - and have been doing that successfully for a while.

• You are comfortable measuring and optimizing the direct business impact of your work.

• You are interested in learning about the healthcare industry and helping us improve the care millions of people receive.

• You are scrappy, and love solving hard problems that matter.

• You are experienced with SQL, handling large-scale data, and are comfortable with at least one programming language (Python, R, etc.).

• You have experience building ML models using modern ML approaches like Neural Nets or Tree-ensembles from scratch for new applications - making decisions relating to which supervised labels to use, the metric to optimize for, and the features likely to be useful.

• You are a critical thinker who can be strategic without losing attention to detail.

• You are comfortable taking the initiative and owning projects from start to finish.

• You can build positive relationships based on trust and value delivered.

The base salary for this position will vary based on an array of factors unique to each candidate such as qualifications, years and depth of experience, skill set, certifications, etc. The base salary range for this role is $180k-250k. We are hiring for different seniorities, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks.

Equal Employment Opportunity at Machinify

Machinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.

We’re seeking an ML Platform Engineer to join our AI focused healthcare startup. Our engineering team is composed of some of the best and brightest engineers & data professionals. They are responsible for writing code that has a massive impact on our customers, healthcare users, and future product lines. Our teams are collaborative, high-performing, curious, aligned to our product goals, and impactful towards the success of the business. We build highly performant ML and AI products that are transforming the landscape of healthcare

What you’ll do:

• Build data platforms that are extensible, scalable, and secure

• Recognize and prioritize between customer deliverables & tech debt to develop a sustainable software suite of products.

• Enjoy designing and architecting complex frameworks for applying ML techniques to large data volumes and simplifying labor-intensive processes

• Deliver resilient enterprise software solutions

What you’ll bring:

• Extensive experience in the field of application programming

• ML background

• Working experience writing SQL queries.

• Java, Scala, Python, C++, C# -- are a plus

• Strong CS foundation (data structures, asynchronous programming)

• Strong test writing discipline

• Experience with reading and understanding complex enterprise-grade code and quickly contributing to it, and suggesting improvements.

• Critical thinking and problem solving skills working in a high growth environment

• Comfortable with ambiguity and taking the initiative when required

• BS or MS in Computer Science (or equivalent experience)

The salary for this position is based on an array of factors unique to each candidate: Such as years and depth of experience, set skills, certifications, etc. The base salary range for this role is $170k to $230k. We are hiring for different levels, and our Recruiting team will let you know if you qualify for a different role/range. Salary is one component of the total compensation package, which includes meaningful equity, excellent healthcare, flexible time off, and other benefits and perks to meet the needs of each individual.

Equal Employment Opportunity at Machinify

Machinify is committed to hiring talented and qualified individuals with diverse backgrounds for all of its positions. Machinify believes that the gathering and celebration of unique backgrounds, qualities, and cultures enriches the workplace.

Work you might work on

• Pre-training: Distributed training across large GPU clusters
• Inference: Optimizing inference throughput of a custom neural net architecture
• RL: Continual learning to train AI models on user feedback
• Tool use: Implement interfaces to allow our AI models to interact with real-world tools or APIs
• Algorithms: Designing, testing, and optimizing new neural net architectures
• Internet-scale data: E.g. scraping much of YouTube

Magic's culture

• Integrity. Words and actions should be aligned.
• Hands-on. Most of us have previously led engineering teams. At Magic, there are no managers. We all spend the vast majority of our time on engineering. If you want to solve hard problems, Magic is the right place for you.
• Teamwork. We move as one team, not N individuals.
• Focus. Ethically deploy AGI. Everything else is noise.
• Quality. We have high standards for ourselves and our products. Magic should feel like magic.

Benefits and perks

• Benchmark-based compensation in the 75th or 90th percentile, including base salary, equity, and benefits
• Flexible working hours
• In-person (London, SF, NYC, or Vienna) or remote
• A small, fast-paced, highly focused team

Your Role

What You’ll Do

Your Role

What You’ll Do

AI Research Residency

Location: New York, NY (Hybrid or Remote)

Duration: 6-12 Months with the possibility of extension

Compensation: Competitive salary with benefits

About The Residency:

The AI Research Residency program presents an exclusive 6-12-month opportunity to accelerate your career in modern AI research. As an AI Research Resident at Normal Computing, you'll have the incredible opportunity to collaborate with our world-class research team in bringing to life a full-stack physics-based AI platform. Your role will involve developing cutting-edge algorithms and hardware paradigms for AI, pushing the boundaries of what's possible.

Specifically, you will:

• Interface with our world-class research team focused on developing a full-stack physics-based AI platform.

• Explore cutting-edge generative AI tools for novel applications

• Research and develop new algorithms and hardware paradigms for AI.

• Conduct numerical benchmarking of algorithmic and hardware proposals.

• Optimize hardware speedups over state-of-the-art and characterize the impact of hardware noise.

• Investigate commercial applications that stand to benefit from Normal’s physics-based AI platform.

If you're ready to be on the frontier of AI research and share our vision for the synergy between physics and AI, we invite you to apply to our AI Residency Program and be part of the exciting future of AI at Normal Computing.

The experience we’re looking for:

• Experience with large-scale numerical simulations, including benchmarking of ML algorithms and training of ML models.

• Experience with modern AI methods, such as probabilistic ML, Bayesian reasoning, sampling algorithms, and generative AI models.

• Familiarity with classical physics formalism, differential equations, and stochastic processes.

• Familiarity with characterizing the impact of noise and imperfections on algorithmic performance.

• Familiarity with data science applications and specific use cases of ML methods.

• Proficiency in at least one programming language, with a preference for those commonly used in ML or scientific computing such as Python or C++.

• Familiarity with TensorFlow, PyTorch, Jax, NumPy, Pandas, or similar ML/scientific libraries.

Residency FAQs:

Is this a part-time or full-time program?

• Our residency is a full-time position lasting in duration between 6-12 months.

Can I be enrolled as a student at a university or work for another employer during the residency?

• No, the residency can’t be completed simultaneously with any other obligations.

I have been out of school for several years. Am I eligible to apply?

• Yes. We will consider applications from various backgrounds.

Is this a paid residency?

• Yes. Residents are paid a competitive salary.

Will I receive benefits during the Residency?

• Yes, residents are eligible for most benefits, including medical (Depending on location).

Will I be required to relocate for this residency?

• Absolutely not. Residents are encouraged to work on-site at our New York office, however we are a distributed team and you are welcome to work from wherever you are currently located.

What options will be open to me at the end of the program?

• While there is no guaranteed conversion to full-time employment, depending on the success of your residency, it would be our hope that there could be an opportunity to explore a full-time role at Normal Computing.

Additional Information:

Normal Computing is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Normal Computing is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accomodations@normalcomputing.ai

About The Role

We are seeking an experienced Sr. ML Engineer to join our team. In this role, you will be responsible for developing and implementing cutting-edge probabilistic machine learning models and algorithms that solve real-world problems for our clients. You will work closely with our research scientists, data scientists, and software engineers to deliver high-quality solutions that meet the needs of our clients.

Responsibilities:

• Develop and implement state-of-the-art probabilistic machine learning models and algorithms to solve real-world problems.

• Explore Bayesian and non-Bayesian approaches to Reliable Deep Learning: for example, uncertainty-aware algorithms for diverse and quality-filtered generations, adaptive or distilled algorithms for fast generations, and techniques for probing and model and training quality understanding

• Work closely with the engineering team to build seamless features and integrations for core Probabilistic ML platform

• Collaborate with research scientists and data scientists to develop new models and techniques for probabilistic machine learning..

• Stay up-to-date with the latest research and industry trends in probabilistic machine learning.

Qualifications:

• Applied experience with machine learning, preferably modern deep learning architectures (e.g. Transformers, CNNs, vision-language models, deep reinforcement learning)·

• Experience with machine learning training objectives beyond accuracy (e.g. Bayesian learning, meta-learning, value-at-risk, robustness, distribution shift, class imbalance, fairness)

• Experience with at least one programming language (preference for those commonly used in ML or scientific computing such as Python or C++).

• Experience using TensorFlow, PyTorch, Jax, NumPy, Pandas or similar ML/scientific libraries.

• Familiarity with probabilistic programming languages (e.g. Tensorflow Probability, Pyro)

Preferred qualifications:

• Experience and participation in a team driving a project from – conception to an experimental idea – to a proof-of-concept – to a launched product feature.

• Experience in cross functional collaboration, with research teams, product teams, and external partners and stakeholders

• Experience with large-scale Bayesian modeling and inference

• Comfort with probabilistic programming languages (e.g. Tensorflow Probability)

• Experience in cross functional collaboration, with research teams and product teams.

Additional Information:

Normal Computing values diverse perspectives and experience. We encourage you to apply to this role if you feel you would be a good fit, even if you do not meet all of the requirements listed.

This role will receive a competitive salary + benefits + equity.

NY Est. Base Annual Range: $140,000-$200,000

A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, and location. Final offer amount may vary from the amount listed above.

Normal Computing is an equal opportunity employer. We are committed to building a diverse and inclusive workforce and do not discriminate based on race, religion, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other legally protected characteristics, Normal Computing is committed to providing reasonable accommodations for candidates with disabilities who need assistance during the hiring process. To request a reasonable accommodation, please email accomodations@normalcomputing.ai

Overview

We hire people from diverse backgrounds and are always looking for employees who bring fresh ideas to our space. Passion is paramount, and at Notable, you will get to work with other talented people who aim to set the new standard for innovation in healthcare.

As an ML/AI engineer at Notable, you’ll work on developing and deploying machine learning models which provide the intelligence-powering robotic processes that underpin critical healthcare workflow automation. The types of AI tasks range from natural language understanding, including document entity extraction, reading comprehension, to computer vision for robotic process automation, such as object detection and optical character recognition. You’ll work closely with the product development team to define ML systems tailored to our needs, help us build the necessary data and computing infrastructure, and ship new solutions to enable intelligent automation.

We look for smart people who can implement well crafted solutions to complex problems in a fast-paced environment, and who can help us attract more smart people. We don't expect you to have experience with our stack (Google Cloud Platform, Python, Tensorflow, Kubeflow, PyTorch, FastAPI, Kubernetes), but we do look for demonstrated mastery of your chosen development stack and a desire to learn new technologies.

Day-to-day responsibilities:

• Work with the product development team and product managers to define scope of work, timeline and product specifications

• Work with backend engineers to deploy, maintain and scale AI models

• Define interfaces between the microservices that runs and delivers AI models

• Discover, collect, clean and transfer data to train AI models

• Experimentation of different AI models, methodologies, frameworks and communicate critical evaluation metrics to product teams.

• Explore, refine, improve best practices within the ML team

• Push the boundaries of ML and AI and innovate on how to best leverage existing technologies to solve new problems

Experience:

• 5+ years of experience working in a relevant role

• Demonstrated ability to translate business requirements and metrics into machine learning model specifications

• Quickly prototype new models from open-sourced code and demonstrate results

• Ability to design and train new model architectures for complex data

• Experience working with real-world data: large, messy, incomplete, irregular, etc.

• Experience working with a mix of structured and unstructured data

• Proficiency with Python and the standard ML stack (numpy, pandas, scikit-learn)

• Experience with a deep learning package, e.g. Tensorflow, PyTorch

• Experience deploying ML models in production

Beware of job scam fraudsters! Our recruiters use @notablehealth.com email addresses exclusively. We do not conduct interviews via text or instant message and we do not ask candidates to download software other than Zoom, to purchase equipment through us, or to provide sensitive personally identifiable information such as bank account or social security numbers. If you have been contacted by someone claiming to be me from a different domain about a job offer, please report it as potential job fraud to law enforcement and contact us here.

Overview

Onebrief makes military planning seamless and represents a shift in paradigm for future military decisions. It is an all-in-one tool that supports both the creative and process-oriented aspects of military planning. In Onebrief, planners use maps, boards, diagrams, timelines, tables, slide decks and text documents to create their plans—all while sharing a common database. Everything stays in sync, in real time. Our approach has been refined and validated through hundreds of user experiments.

We’re post-revenue ($5M+ in ARR), and our customers include some of the most prestigious military commands around the world. We are backed by Y Combinator (S21) and top-tier VCs, including Caffeinated Capital (Affirm, Docker, Notion, and more). Our elite team combines the best of tech and military talent, including education and experience at Google, Facebook, Twitter, Adobe, MIT, Harvard, Rivian, Delta Force, TOPGUN, and more.

We have a big year ahead of us and can barely keep up with demand. This is an opportunity for you to join us with all the perks of an early employee.

What you will achieve

As our first Machine Learning/AI Engineer, you will be pivotal in shaping and developing our AI infrastructure. This role grants you a unique opportunity to take ownership, apply your knowledge, and make your mark on our company's future direction. With a high degree of autonomy, you will be implementing and refining cutting-edge AI/ML solutions with directly impact on our product's success.

About You

This is an opportunity for candidates with hands-on experience evaluating, fine-tuning, training, and productionalizing modern algorithms and open-source machine learning models. Above all, for ambitious individuals who are ready to embrace the challenges and rewards of being the pioneering ML/AI engineer in a rapidly growing startup.

The ideal candidate is a pragmatic individual with a strong formal background in Machine Learning/AI and a bias towards action.

This is a strategic and high-impact role. You will report directly to Rafa, our CTO.

Core skills: Machine Learning, Artificial Intelligence, Python, TensorFlow/PyTorch, Data Analysis, Statistical Modeling, Natural Language Processing, Systems Architecture, SQL/NoSQL Databases, Git Version Control

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field; Master's or Ph.D. is a plus

• 3+ years of practical experience in developing and implementing Machine Learning/AI models in a professional setting

• Proven experience with open-source ML frameworks (like TensorFlow, PyTorch, or similar)

• You are naturally inclined to apply a design thinking approach to problem solving, and iteratively seek to understand your users, challenge assumptions, redefine problems and create innovative solutions which you can prototype and test

• Most importantly, you are a true Onebriefer:

  • You are obsessed with creating value for real users

  • You are ambitious, scrappy, and a creative problem-solver

  • You learn quickly, work iteratively, and naturally seek collaboration

  • You approach your work with integrity, intellectual honesty, and a low ego

  • You communicate frankly, clearly, and succinctly

  • You thrive as a self-starter, embracing autonomy and ambiguity

  • You are a U.S. citizen

About Us

Our team shares a mission, seeks excellence, and plays to win, with the seriousness and camaraderie of an olympic team. We are in this together, not just because Onebrief will one day be 10x the size of Palantir. We are here to radically improve the future of military decisions, so that the coming decades don’t repeat the previous ones.

Here’s what our team members value most about working here:

• Founders' transparency

• Product and vision

• Nimble leadership

• Challenges and learning opportunities

• Ownership and autonomy

• No non-sense policies and procedures

• Remote-first

What's in it for you

• [SALARY] salary/year

• Equity

• Remote work, flex time, and unlimited PTO

• Health, dental, vision, and life insurance

• 401k

• Parental leave

Ontra is a remote-first company, with access to coworking spaces and offices in a few key cities for employees who may prefer in-person working options. We value connection, investing in opportunities for in-person and virtual gatherings with your Ontra colleagues.

We currently are able to hire exclusively in the locations listed below. Select jobs may have more specific location requirements due to business needs.

United States

Arizona, California, Colorado, Connecticut, Florida, Georgia, Illinois, Massachusetts, Maryland, Minnesota, North Carolina, New Jersey, Nevada, New York, Oregon, Pennsylvania, Tennessee, Texas, Utah, Virginia, Washington

APAC

Hong Kong, Singapore

EMEA

United Kingdom

For this job we are currently only hiring candidates based in the United States.*

About the team & opportunity

Ontra is seeking a Manager, Machine Learning reporting to our Director of Machine Learning.

This role will be responsible for all of the Machine Learning efforts on our Contract Automation team. Our Contract Automation product is our flagship product and the Manager, Machine Learning will have a direct hand in developing industry-changing features for our customers.

If you are someone who thrives in a fast-paced, collaborative environment where you will be implementing best-in-class engineering solutions, we’d love to get to know you!

What you’ll do

• Lead: Oversee a team of Machine Learning Engineers, ensuring projects are completed on time and developing your team’s career growth
• Plan: Developing ML roadmaps and work with stakeholders to gather requirements, define priorities, and strategizing a solution
• Evangelize: Assist in guiding and implementing ML and engineering best practices
• Collaborate: Work closely with teams like ML Platform, Application Engineering, and Product to ensure alignment on strategy and prioritizing

What you’ll bring

• Technical Expertise: 7+ years as an individual contributor and 2+ years in leadership, ideally in a high-growth, scaling organization
• Machine Learning Tooling: Experience with tools and technologies like Python, AWS, PyTorch, DVC, and Hugging Face (preferable)
• Team Player: Ability to lead a team while working alongside them
• Communication Skills: Ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.

Our benefits

• Opportunity to participate in Ontra’s unit-based compensation program
• Medical, dental, and vision insurance base plans at no additional cost
• Employer-sponsored retirement plans
• Monthly phone and internet reimbursement (equivalent of $100 USD)
• Annual professional development reimbursement (equivalent of $2K USD)
• 4 months (16 weeks) of parental leave
• Unlimited paid time off
• Twice-weekly lunch perk

Inclusivity

Ontra is committed to the full inclusion of all qualified individuals. As part of this commitment, Ontra will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact talent@ontra.ai.

Pay transparency

Ontra publishes salary ranges on our salary board here: https://bit.ly/3UjAOE3, which currently includes estimated annual cash salary ranges for candidates based in Colorado and New York City, in accordance with applicable laws and regulations.

Ontra leverages current market data to determine compensation, so posted figures are subject to change as new market data becomes available.

Ontra factors in your location when benchmarking compensation for most roles. If you are not located in Colorado or New York City and have been selected to participate in our interview process, we encourage you to speak with your recruiter about compensation for the role during an initial conversation.

In addition to cash salary, the total compensation package Ontra offers includes unit-based compensation (if applicable). Certain roles in our sales and account management departments may also be eligible to receive variable compensation or commission.

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About the Team

OpenAI’s Superalignment Team is working on technical approaches to ensure that superintelligence–an AI system vastly smarter than humans–follows human intent.

Through scientific experimentation, we explore the scalability of alignment techniques and identify potential breaking points. Our approach to alignment research includes a range of different projects; some of these will help us improve the alignment of our models and others will allow us to validate how aligned our models actually are:

• Scalable oversight: How can we best leverage AI systems to assist evaluation of other AI systems on difficult tasks?
• Generalization: Can we understand and control how our models generalize from easy tasks that humans can supervise to hard tasks that humans cannot?
• Automated interpretability: Can we use AI to explain how LLMs work internally?
• Robustness: How can we train our models to be aligned in worst-case situations?
• Adversarial testing: If we deliberately train deceptively aligned models as testbeds, can our oversight techniques, interpretability tools, and evaluations detect this misalignment?

We want to figure out how to spend vast amounts of compute to solve this problem, in particular by automating alignment research itself.

About the Role

We are seeking Research Engineers to help design and implement experiments for alignment research. Responsibilities may include:

• Writing performant and clean code for ML training.
• Independently running and analyzing ML experiments to diagnose problems and understand which changes are real improvements.
• Writing clean non-ML code, for example when building interfaces to let workers interact with our models or pipelines for managing human data.
• Collaborating closely with a small team to balance the need for flexibility and iteration speed in research with the need for stability and reliability in a complex long-lived project.
• Understanding our high-level research roadmap to help plan and prioritize future experiments.
• Implement experiments to measure the effectiveness of scalable oversight techniques such as AI-assisted feedback and Debate
• Studying generalization to see when AI systems trained on easy problem can solve hard problems
• Managing large datasets from interpretability experiments and creating visualizations to explore interpretability data
• Investigating situations when training against a reward signal causes model outputs to deteriorate
• Exploring methods to understand and predict model behaviors, such as finding inputs causing anomalous circuits or catastrophic outputs
• Designing novel approaches for using LLMs in alignment research

You might thrive in this role if you:

• Are excited about OpenAI’s mission of building safe, universally beneficial AGI and are aligned with OpenAI’s charter
• Want to use your engineering skills to push the frontiers of what state-of-the-art language models can accomplish
• Possess a strong curiosity about aligning and understanding ML models, and are motivated to use your career to address this challenge
• Enjoy fast-paced, collaborative, and cutting-edge research environments
• Have experience implementing ML algorithms (e.g., PyTorch)
• Can develop data visualization or data collection interfaces (e.g., JavaScript, Python)
• Want to ensure that powerful AI systems stay under human control

Compensation, Benefits and Perks

The annual salary range for this role is $245,000 – $450,000. Total compensation also includes generous equity and benefits:

• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• 401(k) plan with 4% matching
• Unlimited time off and 18+ company holidays per year
• Paid parental leave (20 weeks) and family-planning support
• Annual learning & development stipend ($1,500 per year)

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 any other legally protected status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

About the Team

OpenAI’s Superalignment Team is working on technical approaches to ensure that superintelligence–an AI system vastly smarter than humans–follows human intent.

Through scientific experimentation, we explore the scalability of alignment techniques and identify potential breaking points. Our approach to alignment research includes a range of different projects; some of these will help us improve the alignment of our models and others will allow us to validate how aligned our models actually are:

• Scalable oversight: How can we best leverage AI systems to assist evaluation of other AI systems on difficult tasks?
• Generalization: Can we understand and control how our models generalize from easy tasks that humans can supervise to hard tasks that humans cannot?
• Automated interpretability: Can we use AI to explain how LLMs work internally?
• Robustness: How can we train our models to be aligned in worst-case situations?
• Adversarial testing: If we deliberately train deceptively aligned models as testbeds, can our oversight techniques, interpretability tools, and evaluations detect this misalignment?

We want to figure out how to spend vast amounts of compute to solve this problem, in particular by automating alignment research itself.

About the Role

As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the Superalignment team, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company.

We are seeking Research Scientists to help design and implement experiments for alignment research. Responsibilities may include:

• Designing experiments to measure the effectiveness of scalable oversight techniques such as AI-assisted feedback and Debate
• Studying generalization to see when AI systems trained on easy problems can solve hard problems
• Managing large datasets from interpretability experiments and creating visualizations to explore interpretability data
• Developing experiments to test how well chain of thought reasoning reflects model cognition
• Investigating situations when training against a reward signal causes model outputs to deteriorate
• Exploring methods to understand and predict model behaviors, such as finding inputs causing anomalous circuits or catastrophic outputs
• Designing novel approaches for using LLMs in alignment research

You might thrive in this role if you:

• Are excited about OpenAI’s mission of building safe, universally beneficial AGI and are aligned with OpenAI’s charter.
• 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
• Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects
• Possess a strong curiosity about aligning and understanding ML models, and are motivated to use your career to address this challenge
• Enjoy fast-paced, collaborative, and cutting-edge research environments
• Have experience implementing ML algorithms (e.g., PyTorch)
• Can develop data visualization or data collection interfaces (e.g., JavaScript, Python)
• Want to ensure that powerful AI systems stay under human control

Compensation, Benefits and Perks

The annual salary range for this role is $245,000 – $450,000. Total compensation also includes generous equity and benefits:

• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• 401(k) plan with 4% matching
• Unlimited time off and 18+ company holidays per year
• Paid parental leave (20 weeks) and family-planning support
• Annual learning & development stipend ($1,500 per year)

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 any other legally protected status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI.

About the Role

As a Research Engineer here, 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.

The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future.

We expect you to:

• Have strong programming skills
• Have experience working in large distributed systems
• Be excited about OpenAI’s approach to research

Nice to have:

• Interested in and thoughtful about the impacts of AI technology
• Past experience in creating high-performance implementations of deep learning algorithms

Compensation, Benefits and Perks

The annual salary range for this role is $200,000 – $370,000. Total compensation also includes generous equity and benefits.

• Medical, dental, and vision insurance for you and your family
• Mental health and wellness support
• 401(k) plan with 4% matching
• Unlimited time off and 18+ company holidays per year
• Paid parental leave (20 weeks) and family-planning support
• Annual learning & development stipend ($1,500 per year)

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 any other legally protected status. Pursuant to the San Francisco Fair Chance Ordinance, we will consider qualified applicants with arrest and conviction records.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.