Staff Product Manager, Model Lifecycle & Management

Pinterest
anywhere in the country2026-05-22

About the job

As a Senior Product Manager for Signal Lifecycle within Trust & Safety, you'll own the product strategy for the ML platform that powers how Pinterest trains, evaluates, deploys, and measures content safety models at scale. You'll lead the development of ML Signal Management — making ML signals first-class entities with unified metadata and identity across systems. Partnering deeply with ML engineering, data science, content safety, and enforcement systems, you'll drive a platform whose scope is expanding from T&S into content quality, ads safety, and beyond.

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

Qualifications

Minimum

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

Preferred

No preferred qualifications listed.