ML Engineering Leader - Next-Gen Recommendations

Pinterest; San Francisco (CA); Hybrid; USD 228,000 - 469,000; Full time

Job summary

Pinterest is seeking an engineering leader to helm a team of ML researchers and engineers within the Applied Science group. You will drive the roadmap for next-generation recommender systems and oversee turning research into scalable production capabilities.

The role requires deep ML expertise, strong leadership, and a track record of delivering high-impact AI solutions at web scale, with collaboration across core engineering, ads, data science, and infrastructure teams.

Qualifications

• 7+ years of post-graduate and industry ML experience on web-scale data.
• 3+ years of direct people management experience.
• Track record delivering high-impact initiatives across multiple product areas.
• Ability to transform vague, ambiguous questions into well-defined projects with clear success metrics.
• Publications in ML/AI, data science, or related fields are a plus.

Responsibilities

• Own the technical roadmap and strategic vision for Pinterest's next-generation recommendation systems.
• Research to production: transition breakthrough ML research into production-ready systems.
• Lead and develop a talented team of ML researchers and engineers specializing in recommendation systems.
• Collaborate with Core Engineering, Ads, Infrastructure, Content, and Data Science teams to prototype, build, and scale solutions.

Skills

Team leadership

ML expertise

Data-driven

Communication

Hiring & mentoring

Education

MS/PhD in CS/ML/NLP/Statistics

Tools

Python

ML frameworks

Job description

Pinterest is seeking an engineering leader to helm a team of ML researchers and engineers within the Applied Science group. You will drive the roadmap for next-generation recommender systems and oversee turning research into scalable production capabilities.

The role requires deep ML expertise, strong leadership, and a track record of delivering high-impact AI solutions at web scale, with collaboration across core engineering, ads, data science, and infrastructure teams.