# Staff Product Manager, Model Lifecycle & Management

**Company:** [Pinterest](https://hotfix.jobs/companies/pinterest)
**Location:** San Francisco, CA
**Role:** Product Management
**Salary:** $165k – $339k/yr
**Experience:** 5+ years
**Skills:** Product Management, Ml Platform Management, Model Lifecycle Infrastructure, Ml Tooling, Data Analysis, SQL, Model Evaluation, Precision/Recall/Fpr, Systems Thinking, Cross-Functional Leadership
**Posted:** 2026-05-22

> Own product strategy for Pinterest's ML platform powering content safety model training, evaluation, deployment, and measurement. Lead ML Signal Management and lifecycle infrastructure in partnership with ML engineering and data science teams.

## Job Description

## What you'll do
- 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

## What we're looking for
- 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

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