Technical Recruiter

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 Finance Bench , Lynx , Simple Safety Tests  , Copyright Catcher , 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.

We're building an exceptional team, and hiring is one of the most important things we do. As we scale, we're looking for a Technical Recruiter to own how we find, evaluate, and close the researchers and engineers who will do this work.

This is not a role where you post a req and work an inbound queue. You'll own the end-to-end hiring process for research and engineering roles: building the pipeline, partnering with hiring managers and the co-founders on what the role actually is, and closing candidates who have other options. The people we hire are among the most heavily recruited in technology.

Reaching them takes real fluency in what they work on — enough to read a paper's contribution, tell a strong open-source record from a busy one, and hold a credible conversation with an RL researcher and an infrastructure engineer in the same afternoon. Templates do not work on this market. Judgment does.

The best person for this role has an opinion before the hiring manager does, sources the people who aren't looking, and holds the bar in a room full of founders who want the req filled. You use AI aggressively to take the mechanical work off your plate, and you spend the hours you win back on the calls only a person can make.

In this role, you will:

• 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.

The number one qualification to succeed in this machine learning course is gumption  - John Lafferty, CS Professor at Yale

Above all, we look for a proactive mindset, willingness to learn, unlimited energy, and relentless optimism. You are a great fit if you have a background in the following:

• You have 5+ years of full-cycle technical recruiting, including time at a startup where the process did not already exist.
• You have hired engineers or researchers…