Job description

ABOUT US Foundry Robotics is building an AI-native robotics manufacturing company focused on deploying advanced assembly and production capability for leading robotics companies and national-security-critical hardware. Basically, we're building robots that build robots. Our mission is to rebuild the American manufacturing industry as an AI-first, assembly-focused, dual-use contract manufacturer. As a founding member of our team, you will have a direct and significant impact on our product, culture, and ultimate success. This role is 100% in-person at our office in Emeryville, CA. THE ROLE Foundry's hardest hires are not engineers who answered a job post. They are roboticists and AI/ML researchers whose best work is a paper, a benchmark, or a lab demo — people who are not on the market, do not read job descriptions, and will only take a call from someone who understood what they actually built. This role exists because sourcing that population is a research discipline of its own. You will read the papers. You will know which labs are doing manipulation work that matters, which advisor's students keep landing at the same three companies, and which postdoc is finishing in the spring and has not told anyone yet. KEY RESPONSIBILITIES - Own end-to-end hiring for robotics and AI/ML research: manipulation, perception, controls, learning, and the ML infrastructure around them — research scientists and research engineers alike. - Source from the literature. arXiv, CoRL, RSS, ICRA, NeurIPS, ICML and CVPR author lists, acknowledgements, and citation graphs are your candidate database — alongside GitHub, not instead of it. - Build real relationships with university labs and faculty. Advisors decide where their students land more often than recruiters do. - Use AI tooling to 10x your own reach: enrichment, paper-to-profile matching, and personalized outreach at volume that still reads like a human who read the work. We will fund the tools; you have to actually run them. - Refuse to open a req without a competency map. Decompose each role into discrete, assessable skills with the hiring manager, then assign each interviewer exactly one of them. - Build and run interviewer training and calibration for research loops — including how to assess research taste, not just implementation skill. - Own talent competitor analysis against frontier labs, robotics startups, and AV companies, and know honestly why a researcher would choose us over a lab with a bigger compute budget. WHAT WE'RE LOOKING FOR Founder mentality: We love people who build like it’s their own company. You move fast, take ownership, and find a way through when the path isn’t obvious. You have the drive to make big things happen and the judgment to take smart risks along the way. If you prefer a clearly defined lane, a predictable pace, and all the answers before you start, there’s nothing wrong with that—but Foundry might not be the right fit. - 8+ years of technical recruiting, including real time hiring research scientists or research engineers in robotics, AI/ML, autonomy, or an adjacent field. - You read the papers. You can explain what a candidate's work actually contributed, and a researcher would not wince at your summary. - You know the landscape — the labs, the advisors, the conferences, and how people move between them. - You have built faculty and lab relationships that produced hires, not just campus visits. - You are genuinely AI-efficient. You have built or run tooling that multiplied your own sourcing output, and you can walk us through your stack. - You are deeply interested in the technology itself. If what you want is a clean req and a target close date, this is the wrong seat. - You have built a competency map, not just filled one in. You can show us one. NICE TO HAVE (NOT REQUIRED) - A technical background — a degree, a research stint, or self-taught depth you can defend. - Hiring into ITAR-controlled or cleared programs, and familiarity with the constraints that come with them. - Recruiting where research has to survive contact with production. Straight Talk About this Role We practice ethical hiring - The best people in this population are not looking, and most will say no. This is long-horizon relationship building, not pipeline throughput. - You will be asked to assess research quality you cannot fully evaluate yourself, and to build the loop that can. - There is no sourcing team beneath you. You are the senior person and also the person reading arXiv on a Tuesday night. You should be able to sell equity at a young company. Cash packages here are not "Big Tech" money, so you'll need to know exactly what makes Foundry different How we hire - How we hire, including how we will hire you: each interviewer digs into one skill and reports back on just that. The hiring - manager pulls it all together and decides. We are not measured on speed-to-fill. We are measured on whether the people - we hired are still performing 12 to 18 months later. A bad hire is worse than no hire, and we would rather be held to that. WHY JOIN US? This is one of the only places where world-class manufacturing operators, mechanical engineers, robotics researchers, and software engineers sit in the same room — building production systems together. We are committed to being deeply embedded in the U.S. industrial base. Our focus is simple: build adaptive robotic assembly systems that make American manufacturing scalable, resilient, and competitive again. If you want to run a mature, well-defined commercial org, this may not be the role. If you want to build the commercial engine that brings AI-driven manufacturing to every industrial and energy customer in America — this is it. The base salary range for this full-time position in the location of Emeryville is: $170,000—$205,000 USD Compensation packages at Foundry Robotics for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Foundry Robotics employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, and generous PTO. Foundry Robotics is an equal opportunity employer. We evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.

Requirements

Must-haves

Own end-to-end hiring for robotics and AI/ML research: manipulation, perception, controls, learning, and the ML infrastructure around them — research scientists and research engineers alike.
Source from the literature. arXiv, CoRL, RSS, ICRA, NeurIPS, ICML and CVPR author lists, acknowledgements, and citation graphs are your candidate database — alongside GitHub, not instead of it.
Build real relationships with university labs and faculty. Advisors decide where their students land more often than recruiters do.
Use AI tooling to 10x your own reach: enrichment, paper-to-profile matching, and personalized outreach at volume that still reads like a human who read the work. We will fund the tools; you have to actually run them.
Refuse to open a req without a competency map. Decompose each role into discrete, assessable skills with the hiring manager, then assign each interviewer exactly one of them.
Build and run interviewer training and calibration for research loops — including how to assess research taste, not just implementation skill.
Own talent competitor analysis against frontier labs, robotics startups, and AV companies, and know honestly why a researcher would choose us over a lab with a bigger compute budget.
8+ years of technical recruiting, including real time hiring research scientists or research engineers in robotics, AI/ML, autonomy, or an adjacent field.
You read the papers. You can explain what a candidate's work actually contributed, and a researcher would not wince at your summary.
You know the landscape — the labs, the advisors, the conferences, and how people move between them.
You have built faculty and lab relationships that produced hires, not just campus visits.
You are genuinely AI-efficient. You have built or run tooling that multiplied your own sourcing output, and you can walk us through your stack.
You are deeply interested in the technology itself. If what you want is a clean req and a target close date, this is the wrong seat.
You have built a competency map, not just filled one in. You can show us one.
A technical background — a degree, a research stint, or self-taught depth you can defend.
Hiring into ITAR-controlled or cleared programs, and familiarity with the constraints that come with them.
Recruiting where research has to survive contact with production.
Straight Talk About this Role
We practice ethical hiring
The best people in this population are not looking, and most will say no. This is long-horizon relationship building, not pipeline throughput.
You will be asked to assess research quality you cannot fully evaluate yourself, and to build the loop that can.
How we hire, including how we will hire you: each interviewer digs into one skill and reports back on just that. The hiring
manager pulls it all together and decides. We are not measured on speed-to-fill. We are measured on whether the people
we hired are still performing 12 to 18 months later. A bad hire is worse than no hire, and we would rather be held to that.

Nice-to-haves

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Dental

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