Manager, Machine Learning Research Scientist, Genai

Scale AI Scale AI · Data AI · San Francisco, CA · Research

Manager for a GenAI research team focused on evaluation, post-training, agents, and RL environments. The role involves leading a team, defining research roadmaps, driving execution, and collaborating cross-functionally. Requires a strong research background with publications and experience in fast-paced environments.

What you'd actually do

  1. Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).
  2. Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
  3. Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
  4. Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
  5. Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.

Skills

Required

  • 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
  • A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
  • Experience and track of recording in landing major research impacts in a fast-paced environment
  • Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.
  • Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

Nice to have

  • PhD or equivalent preferred

What the JD emphasized

  • publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.)
  • Experience and track of recording in landing major research impacts in a fast-paced environment
  • Experience leading or managing research teams.

Other signals

  • leading research teams
  • driving execution from prototyping to deployment
  • shaping how next-generation AI is built, measured, and deployed