Technical Recruiter

Patronus AI, Inc.•San Francisco, CA

4d•$160,000 - $210,000•Onsite

About The Position

Patronus AI is a frontier lab developing simulation research and infrastructure to accelerate progress toward human-aligned AGI. We are on a mission to simulate all of the world’s intelligence. We are the team behind some of the earliest and most influential research in AI evaluation like FinanceBench, Lynx, SimpleSafetyTests, CopyrightCatcher, Humanity’s Last Exam, and more. We are formerly AI researchers and engineers from companies like Meta AI, Amazon AGI, and Google. Our customers include foundation model labs and Fortune 500 enterprises like Adobe. We are backed by top-tier investors like Lightspeed Venture Partners, Notable Capital, Stanford University, Noam Brown, Gokul Rajaram, and more.

Requirements

5+ years of full-cycle technical recruiting, including time at a startup where the process did not already exist.
Hired engineers or researchers in a market where every good candidate had other offers.
Can source. Can name the last five people you found who were not applying and not on the first page of results.
Technical fluency to read a resume, a GitHub profile or a paper and form your own view before the hiring manager does.
Close well. Can build a value proposition for a specific person, and are comfortable in a negotiation.
Clear judgment about the bar, and will hold it in a room with founders who want the req filled.
Keep a clean ATS, report pipeline honestly, and can point at the evidence behind your decisions.
Excited about AI and constantly look for ways technology can make you more effective.
Write exceptionally well. Your outreach is the first thing a candidate reads about us.

Nice To Haves

Hired PhD-level researchers and know your way around arXiv, NeurIPS, ICML, ICLR and the people who publish there.
Recruited specifically for reinforcement learning, evaluation, agents or ML infrastructure.
Built your own tooling — scripts, automations, enrichment — rather than waiting for a vendor.
Know Greenhouse well.
Genuine interest in AI safety and evaluation with a realistic view of both the potential and the limits.

Responsibilities

Manage full-cycle recruiting for technical roles across research, platform, product engineering and technical program management — intake through close.
Source the passive market directly. Work from publications, citations, open-source contributions, conference participation, academic networks and referrals, not just keyword searches.
Partner with hiring managers and the co-founders to turn a vague need into a real role: the scope, the bar, the loop, and what a yes actually looks like.
Develop enough domain fluency to evaluate technical qualifications rather than match keywords, and to be a useful second opinion in a debrief.
Close. Build the narrative for each candidate, handle competing offers, and run negotiations alongside the founders.
Own candidate experience end to end. Every candidate, including the ones we pass on, should leave with a high opinion of us.
Use AI aggressively. Automate market mapping, research, outreach drafting, and funnel analysis so more of your time goes to the judgment calls that cannot be automated.
Report on pipeline health, time-to-fill, source effectiveness and offer outcomes, and use that data to change what we do.
Build beyond the role. As you develop context and judgment, take ownership of increasingly ambiguous recruiting and People problems.