Own the strategy for AI-powered ranking, recommendations, and personalization at Strava, working closely with engineering and data science teams.
Posted by employer 4 months ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
Skills & Technologies
What you'll build
Must have
Nice to have
Practical constraints
AI in the day-to-day
Strava's AI/ML team builds intelligence for ranking, recommendations, and generative AI features across the app.
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Joblaze summary
In the role of Staff Product Manager for AI/ML at Strava, the individual will focus on defining and executing the strategy for personalization, ranking, and recommendations within the app. This position requires a strong background in product management, particularly with machine learning and generative AI, to effectively collaborate with engineering and data science teams. Ideal candidates will have experience in shaping domain-level strategies and a proven ability to drive product decisions based on data insights. Strava's commitment to enhancing athlete experiences through AI underscores the importance of this role in their evolving product landscape.
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Quick facts
From the original posting
Strava's AI/ML team builds the intelligence that shapes what each athlete sees and experiences — from ranking and recommendations to the next generation of generative AI features across the app. As we deepen our investment in AI-powered products, we're looking for a Staff PM to own the strategy for ranking, recommendations, and personalization: a high-impact surface with significant value to unlock.
In this role, you'll define the product vision for personalization across Strava's core experiences, partner deeply with ML engineering and data science to turn model capabilities into products athletes love, and contribute to Strava's broader generative AI strategy. You'll operate with a high degree of autonomy, set direction for a domain, and work across Product, Engineering, and Design to bring the most important bets to life.
We follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office, three days per week.
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.
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.
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