Staff Product Manager, AI/ML

Strava

Staff Product Manager for Strava's AI/ML team, focusing on personalization and product strategy. Collaborates with engineering and data science to enhance athlete experiences through generative AI.

Posted 6/23/2026full-timeSan Francisco • California • 🇺🇸 United StatesLead💰 $250,000 - $270,000 per yearWebsite

About the role

Key responsibilities & impact

Define and own the domain strategy and roadmap for ranking, recommendations, and personalization across Strava's core athlete experiences.
Identify and prioritize high-value GenAI and ML product opportunities across the app, and build a pipeline of bets that connect to company-level priorities.
Partner closely with ML engineering and data science to translate model capabilities, evaluation criteria, and technical trade-offs into clear, shippable product decisions.
Build and drive experimentation and measurement frameworks that demonstrably improve relevance, engagement, and athlete outcomes.
Align stakeholders across Product, Engineering, and Design on strategy and priorities, resolving ambiguity and keeping complex initiatives moving.
Contribute to the broader AI/ML product strategy, including identifying where generative AI can meaningfully improve the athlete experience across Strava's surfaces.

Requirements

What you’ll need

Substantial product management experience, including meaningful time shipping ML-powered products such as ranking, recommendations, personalization, search, or feeds at scale.
Deep fluency in modern ML and generative AI — enough to engage substantively with engineers and data scientists on models, evaluation, and data pipelines, and to make sound product trade-offs.
A track record of owning domain-level strategy end-to-end, not just executing within a defined roadmap.
Strong experimentation and measurement instincts, with demonstrated ability to use data to drive measurable improvements in relevance and engagement.
The ability to align and influence senior stakeholders across functions without authority, and to bring clarity to complex, ambiguous problem spaces.
A low-ego, partnership-oriented approach to working with technical and design partners.
Experience productizing emerging or research-stage capabilities into reliable, user-facing features is a plus.

Benefits

Comp & perks

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Hard Skills & Tools

product managementmachine learninggenerative AIrankingrecommendationspersonalizationdata pipelinesexperimentation frameworksmeasurement frameworksdata-driven decision making

Soft Skills

stakeholder alignmentinfluence without authorityproblem-solvingpartnership-orientedcommunicationambiguity resolutioncollaborationstrategic thinkingleadershipadaptability