Director, Enterprise Machine Learning & Research

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

Director of Enterprise ML at Scale AI, leading research scientists and engineers in GenAI initiatives. The role involves defining and driving a multi-year research roadmap, collaborating cross-functionally, and communicating research outcomes. Focus is on turning research into production-ready systems, with experience in evaluation, post-training, agents, and RL environments. Requires strong research background, publications, and team leadership experience.

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

  • Machine learning
  • Deep learning
  • Generative models
  • Agent/RL systems
  • Research leadership
  • Team management
  • Communication skills
  • Stakeholder management

Nice to have

  • Building and deploying agent-based, tool-augmented, or workflow-driven LLM systems in enterprise environments
  • Ownership of enterprise AI platforms, internal ML products, or customer-facing AI services at scale
  • Partnering directly with enterprises to identify high-impact use cases and deliver measurable business outcomes

What the JD emphasized

  • 8+ years of hands-on research experience (PhD or equivalent preferred)
  • 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.

Other signals

  • leading research teams
  • defining research roadmap
  • driving execution from prototyping to deployment
  • publishing research
  • building and deploying agent-based systems