Pinterest

Staff Product Manager, Model Lifecycle & Management

$165K–$339KFull-time · San Francisco, CA +1 more
✓ Verified live on the employer's own system · added 79 days ago
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Senior

Requirements

Education: Bachelor's degree

Skills & tools

ManagementData AnalysisRest ApisOperationsSQLTeam LeadershipCommunications
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Full job description

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.

  • 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
  • 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

We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

  • This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

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