At Imbue, we care deeply about our team members' personal and individual growth. This role is about supporting and enabling our engineers to grow in the ways that they are excited to grow. You will be focused on mentoring other developers, performing code reviews, pair programming, and generally unblocking people so that they can do their best work. You will help onboard new hires, conduct interviews, and develop cultural best practices to create a truly world-class team.

• Mentoring other engineers, especially junior team members.

• Unblocking individuals. You will be responsible for ensuring that anything that gets in the way of other engineers gets resolved, whether it is a personal issue or a technical one.

• Performing code reviews and providing feedback so that other engineers can continually hone and improve their craft.

• Conducting lots of technical interviews.

• Onboarding new team members, improving that process, and ensuring that new team members feel welcome, safe, and included.

• Highly empathetic. We like everyone to feel comfortable and able to contribute, and you will be a key contributor to that feeling of safety.

• An experienced software developer from whom other engineers are excited to learn.

• Interested in people and culture. You are excited about using and investing in the softer skills that management requires.

• Knowledgeable about machine learning. You don’t need to be a world-famous published researcher, but you should be comfortable with training deep neural networks and much of the latest machine learning theory and practice.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

In this role, you’ll have end-to-end ownership over our entire product. We are still in the very earliest stages of development, so you’ll have the ability to shape our product from beginning to end—not just the technologies that we use, but also the overall direction of our product. You will be responsible for everything to do with product, from user interviews, to prototype development, to ensuring that we have a smooth process for deploying changes.

This role is a particularly good fit for anyone who either has previously been, or would like to be, a founder of a software product company. We are looking primarily for judgment—for someone who can understand what actually matters and then make that happen.

• Conduct user interviews. Shadow users on the job and as they use the product.

• Develop prototypes for entirely new products.

• Deploy new products and quickly generate feedback from both internal and external users.

• Create robust frontend and backend infrastructure to support fast iteration.

• Rapidly iterate and ship new features.

• Motivated by solving real problems for real customers.

• Energized by understanding and talking to users.

• Able to work independently and without explicit directions.

• A great software engineer. You will need to write a considerable amount of software across the stack.

• Familiar with Python.

• Either experienced or interested in being a founder of a software product company.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

We believe that high quality data is the most important part of creating high performance machine learning systems, regardless of whether they are simple classifiers or state of the art reasoning agents. We view this work as one of the most important at the company, and want someone who is solely dedicated to coordinating our efforts across the diverse range of data that matters to us.

In this role, you will lead our data engineering efforts. You will coordinate everything from human data collection processes to the collection, filtering, and preprocessing of raw web data, longer texts, code, and other generated data. You will be responsible for the ultimate quality and quantity of data on which we can train our systems, which is the primary factor in their performance. You will both direct this work, and get into the details yourself to ensure that we are constantly improving our data quality.

• Scan one million physical books and convert them into high quality pretraining data.

• Find 90% of the most useful text available online and make clean training data from it.

• Generate pretraining data in ways that are guaranteed to have low error.

• Measure and understand the quality of each of our datasets.

• Ensure that researchers and engineers can quickly and easily acquire human labels for a dataset.

• Passionate about data. You should be happy to look at and deeply engage with the raw data.

• An excellent software engineer. We care about engineering best practices.

• A great communicator. You will need to coordinate efforts between multiple external organizations and within our own team.

• Familiar with python.

• Work on the most important part of our system

• Work at a place that deeply cares about data quality

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

At Imbue, we leverage large amounts of compute to make our small research team more effective. This role is about enabling and supporting those large-scale compute efforts and all of the other software infrastructure that goes into making research a pleasant, seamless experience for the rest of the team, especially as we scale to increasingly higher scale systems.

One benefit of this role is that, since we have no product or customers, you will not be on-call. All of our engineers are (and will continue to be) sufficiently empowered to fix their own infrastructure issues.

• Prototype and develop infrastructure for increasingly large-scale models

• Create tools and scripts for common research workflows (ex: changing the priority of a currently running job)

• Integrating with new cloud providers and enabling us to run experiments seamlessly across different clouds and physical infrastructure

• Consolidate our logging efforts

• Improve security policies and procedures

• Automate provisioning of new physical servers, NFS, etc

• A good software engineer. We are strong adherents of "infrastructure as code", so you will be writing (and reading) lots of Python, bash, etc.

• Passionate about enabling other engineers and creating good tooling for developers to interact with infrastructure in an automated way.

• Experienced enough with dev ops to be properly opinionated. You should understand the trade-offs of various approaches and technologies, and not be dogmatically tied to a single tool.

• Careful and detail oriented. We do science and care deeply about the correctness of the results. Our infrastructure reflects this--we highly value robustness and ensuring that systems run reliably and correctly.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

As a remote machine learning engineer, you’ll work very closely with a senior member of our research team on cutting-edge deep learning research, infrastructure, and tooling towards the goal of creating general human-like machine intelligence.

• Implement a self-supervised network using contrastive and reconstruction losses.

• Create a library on top of PyTorch to enable efficient network architecture search.

• Open source internal tools.

• Implement networks from newly published papers.

• Work on tools for simple distributed parallel training of deep neural networks.

• Develop more realistic simulations for training our agents.

• Design automated methods and tools to prevent common issues with neural network training (e.g. overfitting, vanishing gradients, dead ReLUs, etc).

• Create visualizations to help us deeply understand what our networks learn and why.

• Very comfortable writing Python.

• Familiar with PyTorch and training deep neural networks.

• Excited to work on open source code.

• Passionate about engineering best practices.

• Self-directed and independent.

• Excellent at getting things done.

• Work directly on creating software with human-like intelligence

• Very generous compensation

• Flexible working hours

• Work remotely

• Time and budget for learning and self improvement

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

In this role you’ll work with our researchers to do cutting-edge deep learning research—conducting experiments, creating infrastructure, and developing tooling & visualizations—with the goal of developing more human-like machine intelligence.

Note: This research role requires being onsite in San Francisco. If you're remote, please take a look at our Machine Learning Engineer (Remote) role, which is more engineering-heavy.

• Implement a self-supervised network using contrastive and reconstruction losses.

• Create a library on top of PyTorch to enable efficient network architecture search.

• Implement networks from newly published papers.

• Run massively parallel experiments to understand all variants of an architecture.

• Develop more realistic simulations for training our agents.

• Create visualizations to help us deeply understand what our networks learn and why.

• Passionate about understanding the fundamentals of intelligence.

• Very comfortable writing Python.

• Excited to be a world-class ML engineer.

• A fan of pair programming.

• Passionate about engineering best practices.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

At Imbue, we are building practical tools on top of foundation models optimized for high-level reasoning, starting with agents that can code. By building on top of these models, we create a tight feedback loop in our research that helps us understand the capabilities and failings of the underlying models as well as the interfaces through which they are served.

In this role, you will be responsible for ideating and creating new tools on top of both our models and public models by rapidly exploring and prototyping your ideas. Through this practical experimentation, you will better understand the underlying capabilities of these models and help develop new paradigms for interfacing with them.

• Work in a research-oriented environment to develop and iterate on prototypes, such as coding agents, through knowledge generation and ideation

• Rapidly incubate and test multiple ideas to gain further insights and validate assumptions about the underlying models

• Conduct experiments, analyze data, and leverage research findings to inform prototyping and ideation

• Create frontend and backend infrastructure to support fast iteration

• Able to generate new ideas, rapidly iterate, and prototype in a high-agency environment

• A very strong engineer who is comfortable building quickly across the stack

• Passionate about interface research, not in terms of traditional UI/UX, but how the capabilities of the underlying AI models impact how users harness them

• Possess a deep understanding or interest in LLMs at a theoretical level

• Comfortable with unconventional approaches to exploring new ideas and prototyping product concepts

• Familiar with Python

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

This role is about investigating the fundamental questions of intelligence, knowledge and understanding in order to develop software with human level intelligence. You will collaborate internally and externally with other researchers, and be supported by a team of research engineers.

• Unsupervised RL

• Self-supervised learning

• Multi-task RL

• Meta-learning

• Continual learning

• Deep learning theory

• Generalization

• Human-like learning

• Network architecture search

• etc.

• A highly accomplished machine learning researcher (e.g., a track record of high quality papers at top conferences like NeurIPS, ICML, ICLR, etc., or equivalent accomplishments in industry).

• Able to create research questions that clarify the nature of the problem being solved, and coordinate a research program to successfully answer those questions.

• Extremely comfortable running ML experiments.

• Able to clearly communicate about your ideas and intuitions.

• Excited to mentor a small team of great research engineers.

• Work directly on answering the fundamental questions of intelligence, learning, and knowledge, free from politics and pressures to publish or commercialize your research.

• Generous compensation, equity, and benefits.

• Actively co-create and participate in a positive, intentional team culture.

• Frequent team events, dinners, off-sites, and hanging out.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

All submissions are reviewed by a person, so we encourage you to include a cover letter. If you have any other work that you can showcase (open source code, side projects, etc), you should certainly include it!

We try to reply either way within a week or two at most (usually much sooner).

We know that talent comes from many backgrounds, and with many different skills and preferences. That’s why we have a hiring process that gives you the ability to showcase yourself in a variety of different ways, depending on what feels best for you.

Much of the work we do at Imbue is effectively pure software engineering. Our perspective is that even machine learning research ends up being about 90% software engineering, so even without any prior machine learning knowledge, there is plenty to contribute as a normal software engineer. Even most of our machine learning research tends towards the software engineering side of the spectrum, as we prefer to automate the types of work that academic researchers typically do (ex: tuning hyperparameters, experimenting with small variations in network architectures, etc).

• Create an automated service for iterating on network architectures. Most of the work is in defining and implementing the search space over network (which are, at the end of the day, just code that defines a graph of computations).

• Implement new tasks in Avalon and related environments. We are constantly extending our systems to add newer, more complex tasks on which to train more capable agents.

• Optimize existing agents and models to make them lower latency and higher throughput.

• Develop improved graphing, debugging, and error handling tools to investigate the myriad ways that neural networks and agents fail.

• Very comfortable writing Python.

• Familiar with PyTorch and training deep neural networks.

• Excited to work on open source code.

• Passionate about engineering best practices.

• Self-directed and independent.

• Excellent at getting things done.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

We believe that high quality data is the most important part of creating high performance machine learning systems, regardless of whether they are simple classifiers or state of the art reasoning agents. Unlike many other organizations, we view this work, and this role, as one of the most important at the company.

In this role, you will work on the most important part of our system--the software infrastructure for collecting, preprocessing, generating, analyzing, and distilling the wide variety of data sources that go into both our primary pretraining data corpus, as well as the datasets for all of the other ancillary and secondary models and system. You will make a meaningful, measurable impact on the performance of our systems, and experience the joy of spending time to make high quality software that makes high quality data.

• Incorporate new sources of high quality text data into our existing data pipelines

• Develop models for accurately classifying and extracting meaningful text from raw html

• Create a high quality OCR pipeline for pulling pretraining text from images and scans

• Collect a ludicrous amount of multimodal data(ex: transcripts for thousands of years of video)

• Design unique data generation pipelines that leverage existing data(ex: convert code from one language to another)

• Integrate multiple annotation service providers into a sensible interface for researchers

• Detail oriented. Data mistakes are easy to make and hard to catch.

• Passionate about data. You should be happy to look at and deeply engage with the raw data.

• An excellent software engineer. We care about engineering best practices.

• Familiar with python.

• Work on the most important part of our system

• Work at a place that deeply cares about data quality

• Work directly on creating software with human-like intelligence

• Very generous compensation

• Flexible working hours

• Work remotely

• Time and budget for learning and self improvement

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

As a systems engineer, you’ll work on pioneering machine learning infrastructure that enables running large numbers of experiments in parallel across local and cloud GPUs, extremely fast training, and guarantees that we can trust experiment results. This allows us to do actual science to understand, from first principles, how to build human-like artificial general intelligence.

You’ll also play a role in open sourcing infrastructure for the machine learning community.

No machine learning experience is required. This role is contract if you're remote, and full-time if you're onsite in San Francisco.

• Abstracting cloud and physical GPU resources.

• Implementing a caching system for models and datasets.

• Profiling and optimizing third-party C++ code.

• Using eBPF for continuous system profiling.

• Turning man pages into bug fixes.

• Creating observability tools for distributed systems.

• Writing shaders, learning about video encoding on the GPU, etc.

• Very comfortable writing Python and reading bash.

• Obsessive about deeply understanding how systems work.

• Happy to debug any weird problem all the way down.

• Familiar with Docker, cloud services, physical servers, systems internals.

• Excited to work on open source code.

• Passionate about engineering best practices.

• Self-directed and independent.

• Excellent at getting things done.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• Spend time learning and pairing with world-class engineers working across diverse problems who are excited share their knowledge to get you up to speed.

For full-time team members onsite in San Francisco:

• Actively co-create and participate in a positive, intentional team culture.

• Frequent team events, dinners, off-sites, and hanging out.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

We are looking for a technical leader who can lead a strong team of versatile engineers both through direct guidance and by example. You will provide guidance to team members on their technical projects, from pair programming and code reviews to empowering them to make higher-level decisions. As an IC as well as a leader and mentor, you will play a key role in determining our technical strategy.

• Code, a lot, as an IC to our technical roadmap.

• Mentor and pair program with other engineers to help them develop their practical skills.

• Perform code reviews and provide feedback so that other engineers can continually hone and improve their craft.

• Help establish best practices and standards in our codebase to improve the quality of our systems.

• Someone who loves to code. This is a hands-on position and is not suitable for those who want to simply oversee projects.'

• Knowledgable and eager to keep up-to-date with best engineering practices.

• Passionate about people, mentorship, and teaching, as a primary responsibility of yours is to help other engineers grow their technical skills.

• Very proficient with Python.

• Knowledgeable about machine learning. You don’t need to be a world-famous published researcher, but you should be comfortable with training deep neural networks and much of the latest machine learning theory and practice.

• Work directly on creating software with human-like intelligence.

• Generous compensation, equity, and benefits.

• $20K+ yearly budget for self-improvement: coaching, courses, conferences, etc.

• Actively co-create and participate in a positive, intentional team culture.

• Spend time learning, reading papers, and deeply understanding prior work.

• Frequent team events, dinners, off-sites, and hanging out.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

The Chief of Staff will work closely with CEO Kanjun Qiu and CTO Josh Albrecht as we scale Imbue. Kanjun herself started her career as the Chief of Staff at Dropbox, scaling the company from 200 to 1300 people.

This is a high-trust role with enormous growth potential. Your job is to do whatever it takes to make Generally Intelligent successful. Your work will cut across strategic initiatives and tactical execution with both internal and external folks.

• Interview machine learning engineers and researchers

• Build relationships with potential partner companies and customers

• Represent Kanjun in internal and external communications, meetings, and events as needed

• Prepare quarterly board materials

• Research and reach out to people in order to build relationships, find guests for our podcast, and surface potential new opportunities

• Take over finance, legal, and HR

• Manage operations team, including assistants, event planners, and office coordinators

• Build systems to streamline operations and support company culture as we grow

• Build and manage press machine and social media marketing

• A fast learner

• Gets stuff done

• Can take on big projects and move them forward with little oversight

• Deep belief that AI today is a historical moment, like the Industrial Revolution or early Internet

• Strong writing skills

• Enjoy talking to people / working through others

• Interest in building an AI community around Imbue

• Experience as a founder

• Experience in BizOps (business operations) at a startup

• Experience in strategy consulting (e.g. McKinsey, BCG), in addition to at a startup

• Experience as an engineer or product manager with a desire to move to the business side

• Studied quantitative fields like math, computer science, physics, or computational biology

Since writing is a core part of this role, we require you to upload 1-2 writing samples in your application. We’ll be evaluating for fluency and clarity of thought. Examples could include:

• A memo outlining strategy for a new product

• An analysis of a business process

• Blog posts or other copy written for external publishing

• etc.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

At Imbue, we take recruiting seriously and take great measures to optimize our process for the benefit of both our team and the candidate. To this end, we are seeking a personable and proficient coder to conduct first-round coding interviews on behalf of our team. You would be responsible for Step 2 in the interview process outlined here. This can be either a full-time or a contract-based, hourly position and is ideal for junior engineers looking to improve their skills.

Important note: If you are looking for a part-time contract and are currently employed elsewhere, please check your contract to make sure this wouldn't be a conflict of interest, or if you need to get written consent to take on this position.

• You are strong in the fundamentals of computer science including algorithms and data structures

• You are proficient in Python and ideally comfortable with 2–3 other languages

• You have an eye for clean, debuggable code and good coding practices

• You are comfortable on video calls (strong wifi and professional interview setting are a must)

• You are able to appropriately guide candidates when they get stuck

• You can commit to a minimum of 10 hours a week

• We will train you on 3 coding problems that you will present to candidates

• You will observe candidates coding in their own environment using whatever resources, libraries, or frameworks they’d like

• You will then submit feedback on the candidate’s performance and a recording of the interview through our ATS (Applicant Tracking System)

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skillsets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).

Here at Imbue, recruiting is mission critical. We believe recruiting is not just about evaluating candidates, but also about understanding them and their journeys on a deep level. And we strive to be thoughtful and as transparent as possible—here’s a blog post explaining our recruiting process in depth.

As our Recruiter/Talent Coach, you will be responsible for owning the candidate experience and growing our team.

No recruiting experience necessary. We’re looking for someone who enjoys connecting with people all day every day, gets stuff done, and is eager to deeply engage with technical topics so that you can discuss them authentically. If you’re hungry, have solid people instincts, and want to play a role in building general AI agents, we can’t wait to meet you!

• You’re endlessly curious about people and enjoy supporting their journeys.

• You’re excited to dive deeper into AI and synthesize technical concepts to a degree that you can explain them to a technical audience (e.g. explaining our roadmap, outlining current research projects, etc.).

• You're high agency, scrappy, and excited to take ownership over building the Generally Intelligent team.

• A background in recruiting is not required and not expected—everything you need to know can be learned on the job

• You’re able to quickly get a sense of a person and their motivations.

• You’re excited to be on Zoom calls with candidates at least 50% of the workday.

• A background in psychology, personal coaching, or other high-interaction professions is a plus (though absolutely not required).

• One of your primary responsibilities will be to conduct initial chats with candidates, though these will be more career coaching sessions than typical recruiter screens. On these calls, you’ll get a sense of the candidate’s motivations, existing skillset, and personal/professional needs. You will also be expected to discuss our company, culture, projects, and roadmap on a deep, meaningful level.

• Supported by a recruiting coordinator, you will manage the end-to-end pipeline of candidates from application to closing the offer. This involves frequent touch points with candidates to support them throughout the process.

• Supported by talent sourcers, you will be responsible for managing the top-of-funnel efforts, including overseeing outreach campaigns, filtering applicants, and working with agencies.

All submissions are reviewed by a person, so we encourage you to include notes on why you're interested in working with us. If you have any other work that you can showcase (open source code, side projects, etc.), certainly include it! We know that talent comes from many backgrounds, and we aim to build a team with diverse skill sets that spike strongly in different areas.

We try to reply either way within a week or two at most (usually much sooner).