Vp, Research

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

VP of Research to lead ML Research function, focusing on frontier evaluations, post-training data science, agentic applications, and trustworthy agent oversight. The role involves shaping technical direction, translating science into production solutions, building and scaling a global team, and partnering with customers and internal teams to drive AI progress and responsible deployment.

What you'd actually do

  1. Lead the ML Research function, responsible for delivery, quality, performance, and roadmap execution
  2. Build and scale a global high-performing team, with an emphasis on initiative ownership and ML excellence
  3. Partner directly with Fortune 100 customers and the GTM team to translate business needs into scalable technical solutions
  4. Collaborate with engineering, product, and delivery teams across Scale to drive cutting edge research
  5. Shape the long-term vision and org design of the ML Research team, aligned with business growth and product evolution

Skills

Required

  • ML Research leadership
  • Team building and scaling
  • Customer partnership
  • Cross-functional collaboration
  • Strategic vision and planning
  • Mentorship
  • Financial and operational understanding
  • Product engineering
  • Infrastructure
  • AI agent systems

Nice to have

  • Experience in high-growth environments
  • Experience structuring and evolving research teams
  • Ability to distill priorities and move teams from ambiguity to execution
  • Comfortable in the weeds and at the executive level

What the JD emphasized

  • lead the ML Research function
  • Build and scale a global high-performing team
  • partner directly with Fortune 100 customers
  • drive cutting edge research
  • Shape the long-term vision and org design
  • Manage and mentor senior ML Research leaders
  • Make rigorous tradeoffs
  • Represent ML Research in cross-functional planning cycles
  • leading ML Research teams
  • scaled research organizations
  • Operates with urgency and clarity
  • experience partnering deeply with sales, delivery, and customer success teams
  • core technical areas—especially product engineering, infrastructure, or AI agent systems

Other signals

  • leading ML research teams
  • translate science into production-ready solutions
  • develops safeguards to deploy them responsibly
  • partner with go-to-market, delivery, engineering, and customers