Recruiter, Ai/ml Research

OpenAI OpenAI · AI Frontier · San Francisco, CA · People

Recruiter role focused on identifying, engaging, and recruiting top AI/ML researchers and technical scientists for OpenAI's research organization. This role acts as a strategic partner, influencing hiring priorities, shaping search strategies, and guiding hiring decisions to support frontier-model research.

What you'd actually do

  1. Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve.
  2. Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist.
  3. Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles.
  4. Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit.
  5. Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains.

Skills

Required

  • Significant experience recruiting within highly technical or specialized environments
  • Deep interest in AI research and a desire to engage directly with global research communities
  • Experience recruiting within highly technical or specialized environments such as ML/AI, distributed systems, infrastructure, scientific computing, or quantitative research
  • Track record of leading complex, ambiguous technical searches from early talent mapping through close
  • Experience navigating high-stakes negotiations with senior technical or research candidates
  • Comfort operating in fast-moving environments where hiring priorities and role definitions may evolve over time

What the JD emphasized

  • highly technical or specialized environments
  • AI research
  • highly technical or specialized environments such as ML/AI, distributed systems, infrastructure, scientific computing, or quantitative research
  • complex, ambiguous technical searches
  • senior technical or research candidates