Staff Product Manager, Model Lifecycle & Management

PinterestSan Francisco, CA
Remote

About The Position

At Pinterest, AI is a powerful partner that augments creativity and amplifies impact. This role focuses on the ML platform that powers how Pinterest trains, evaluates, deploys, and measures content safety models at scale. The Staff Product Manager will lead the development of ML Signal Management, making ML signals first-class entities with unified metadata and identity across systems. This role involves deep partnership with ML engineering, data science, content safety, and enforcement systems, with a platform scope expanding beyond Trust & Safety into content quality and ads safety.

Requirements

  • 5+ years product management experience
  • Experience owning or managing ML platforms, model lifecycle infrastructure, or ML tooling
  • Strong data fluency — comfortable with precision/recall/FPR, evaluation methodology, and model performance measurement
  • SQL proficiency — able to self-serve data investigation and analysis
  • Demonstrated systems thinking — experience with complex interconnected infrastructure serving multiple teams
  • Strong cross-functional leadership — proven ability to drive decisions across ML engineering, data science, and product stakeholders
  • Excellent written and verbal communication of complex ML and infrastructure concepts
  • Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience

Responsibilities

  • Own and drive the Signal Lifecycle product roadmap, including ML Flywheel infrastructure, auto-deployment, model onboarding, golden dataset management, and signal performance measurement
  • Define and ship ML Signal Management — a unified backbone that elevates ML signals into first-class entities with comprehensive metadata, cross-system naming, and API access
  • Partner with ML Engineering to reduce model iteration time through automated retraining, evaluation, and deployment pipelines
  • Own measurement infrastructure — golden dataset strategy, prevalence measurement, model performance dashboards, and experimentation frameworks
  • Lead cross-functional signal strategy with Content Safety, Enforcement Systems, Data Science, and Operations
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