Staff PM, Applied AI/ML Platform (Equity Available)

Socket.dev; San Francisco (CA); Hybrid; USD 165,000 - 339,000; Full time

Job summary

Pinterest is seeking a Staff Product Manager for Applied Sciences to define roadmaps for representation learning, signals, and recommender systems. You’ll align research, engineering, and product teams to deliver scalable AI-driven experiences across Pinterest.

You will translate scientific advances into product bets, establish adoption metrics, and drive platform health while balancing performance with cost and reliability.

Qualifications

• 7+ years of Product Management experience or equivalent.
• Experience owning a shared ML/AI platform used by internal engineering and product teams.
• Experience shipping AI/ML products into production on high-traffic consumer surfaces.
• Strong platform product instincts and ecosystem thinking.
• Technical credibility with ML/AI teams, with knowledge of representation learning and production readiness.

Responsibilities

• Shape the product vision and roadmap across Pinterest’s Applied Sciences portfolio.
• Partner with teams to ensure new capabilities are broadly adopted and not built in silos.
• Translate roadmaps into product bets with clear success criteria and measurable impact.
• Define and communicate platform value metrics including adoption, quality, time to production, and cost.
• Evaluate modeling tradeoffs and scale innovations sustainably across surfaces.

Skills

Product Management

AI/ML platform ownership

Cross-functional collaboration

Executive communication

Strategic judgment

Technical credibility with ML/AI teams

Education

Bachelor’s degree in Computer Science or equivalent

Job description

Pinterest is seeking a Staff Product Manager for Applied Sciences to define roadmaps for representation learning, signals, and recommender systems. You’ll align research, engineering, and product teams to deliver scalable AI-driven experiences across Pinterest.

You will translate scientific advances into product bets, establish adoption metrics, and drive platform health while balancing performance with cost and reliability.