Principal Technical Recruiter

Who we are

Odyssey is an AI lab pioneering general-purpose world models: causal, multimodal systems that learn to predict and interact with the world over long horizons, while generating real-time, interactive simulations from any starting point. This foundational technology promises to revolutionize robotics, science, healthcare, education, gaming, defense, and beyond.

What we’re looking for

We're looking for a senior technical recruiter to own hiring across research and engineering at Odyssey; ML research, robotics, applied ML, infrastructure, and systems.

Every role is high-impact and every hire is visible to the founders and the technical team, so this feels closer to executive recruiting than high-volume technical sourcing. You'll work directly with research leads, engineering managers, and the founders to identify, attract, and close exceptional talent in the most competitive market in technology.

This is a hands-on individual contributor role. If you've reached manager level and want to get back to the craft of recruiting at a company where every hire matters, this could be a great fit.

What you’ll do

• Take ownership of the entire recruiting lifecycle for research and engineering roles—including ML research, robotics, applied ML, infrastructure, and systems engineering.

• Collaborate directly with founders, research leads, and engineering managers to define role requirements, set the technical bar, and design hiring strategies for each search.

• Source, engage, and successfully close senior researchers and engineers in a competitive market where many candidates have offers from top frontier labs.

• Develop creative, technically informed outreach strategies, such as leveraging paper authorship, conference presentations, GitHub contributions, and lab alumni networks, to attract passive candidates who may not respond to standard recruiter messages.

• Design and continuously refine calibrated technical interview loops, research interviews, screening processes, and debrief procedures for both research and engineering tracks.

• Integrate AI tools (such as Claude, OpenAI, etc.) into your core workflow for sourcing, outreach, screening, and operations.

• Manage the end-to-end candidate experience, ensuring a technically credible and high-touch process for every hire.

Who you are

• Senior-level technical recruiter with significant in-house experience at a high-growth AI, deep-tech, or research-driven technology company.

• Proven track record of end-to-end hiring for research and engineering positions, including researchers, ML engineers, robotics engineers, and senior infrastructure/systems engineers.

• Experienced in conducting high-stakes, high-touch technical searches, where each hire gains direct founder visibility.

• Background in rapidly scaling technical recruiting organizations, with contributions to building key processes, not just following them.

• Strong technical literacy; able to read papers or review repos to identify suitable candidates and ask insightful follow-up questions during screens.

• Extensive technical sourcing expertise—capable of clearly articulating your approach (papers, conferences, lab networks, GitHub), beyond the tools you use.

• Demonstrated success in closing candidates against offers from frontier AI labs and FAANG companies.

• Regular user of AI tools in your recruiting workflow, able to illustrate how these technologies have transformed your approach.

• Naturally curious and quick to learn about emerging technologies—able to effectively communicate and pitch cutting-edge research and robotics to top talent, inspiring their interest.

Bonus

• Experience serving as the first or an early in-house recruiter at a startup, establishing the recruiting function from the ground up.

• Background in recruiting for a frontier AI lab, deep-tech company, or research-focused organization.

• Familiarity with Ashby as an applicant tracking system (ATS).

• Established network among researchers in machine learning (ML), reinforcement learning (RL), robotics learning, or systems for ML.