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Staff Product Manager, AI/ML

Own the strategy for AI-powered ranking, recommendations, and personalization at Strava, working closely with engineering and data science teams.

Location
San Francisco, California, United States
Compensation
Not disclosed
Level
staff
Type
full time · Hybrid

Posted by employer 4 months ago

First seen on Joblaze 1 day ago

Last verified on the company career page 1 day ago

Apply at Strava → Save job Scanned from strava.com

What you'll build

  • Define and own the domain strategy and roadmap for ranking, recommendations, and personalization
  • Identify and prioritize high-value GenAI and ML product opportunities
  • Partner closely with ML engineering and data science
  • Build and drive experimentation and measurement frameworks
  • Align stakeholders across Product, Engineering, and Design

Must have

  • Substantial product management experience
  • Experience shipping ML-powered products
  • Deep fluency in modern ML and generative AI
  • Track record of owning domain-level strategy end-to-end
  • Strong experimentation and measurement instincts

Nice to have

  • Experience productizing emerging or research-stage capabilities

Practical constraints

  • More than half of your time on-site in San Francisco office, three days per week

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.

Joblaze insights

  • Listed yesterday — first seen on Joblaze November 8, 2026. Last confirmed on Strava's careers page November 8, 2026.
  • This exact title is also open at 1 other location at Strava: Strava SF.
  • AI/ML appears in 36.9% of 149 comparable staff product roles in United States; Generative AI appears in 1.3% of 149 comparable staff product roles in United States.

Quick facts

Is the Staff Product Manager, AI/ML role remote?
It's hybrid — Strava expects some on-site time in San Francisco, California, United States.
Where is the role based?
Strava is hiring for this position in San Francisco, California, United States.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Generative AI, Machine Learning.
What seniority level is this role?
Strava targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Staff Product Manager, AI/ML role at Strava.

From the original posting

About This Role

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.

What You'll Do

  • 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.

What You'll Bring to the Team

  • 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.

For more information on benefits please click here.

Why Join Us?

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