Staff Product Manager, AI, Data, ML & Platform
$220,000–$302,500 year
HybridNew York City, New York, United States
Job Summary
Own the path from ML idea to production by running structured discovery with engineers and scientists to prioritize investments across training, deployment, and observability. Drive adoption of AI data agents to accelerate decision-making and measure success through time saved and models shipped rather than demo metrics. Increase trust in core data by defining SLAs, establishing pipeline health, and enforcing access controls and auditability for compliance. Build a durable product-platform operating model with a published roadmap, intake process, and adoption tracking that scales as the function grows.
Required Qualifications
- 8+ years of product management experience
- ownership of complex technical products at Staff or Lead scope
- Technical fluency across data and ML platforms
- experience working directly with data and ML systems
- ability to engage credibly with engineering on architecture tradeoffs
- understanding of modern ML in production
- understanding of model training and deployment
- understanding of feature pipelines
- understanding of evaluation
- ability to translate technical complexity into clear strategic choices
- Experience shipping platform products for internal technical users
- experience with discovery
- experience with success metrics
- experience with adoption
- experience with operational discipline
- Experience shipping in a marketplace or other data-rich product context
- understanding of how upstream data and ML decisions translate into conversion, relevance, and retention
- Cross-functional influence and strategic prioritization
- credibility with senior engineers and data scientists
- ability to negotiate without positional authority
- ruthless sequencing
- clarity about what the team is choosing not to do
- Comfort building an operating model
- established discovery practices
- established intake practices
- established measurement practices
- ability to grow a platform practice beyond its initial domain
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