Staff Technical Recruiter

Foundry Robotics•Emeryville, CA

3d•Onsite

About The Position

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.

Requirements

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 Haves

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.

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.