Primary record

Engineering Manager, ML and Data Products

Strava Indexed employerStrava SF
Source-hosted applyChecked 2h ago$240K–$260K/yrFull-Time
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Workplace

hybrid

Employment

Full-Time

Published

May 27, 2026

Closes

No date supplied

The role

ABOUT STRAVA Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today. Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward. We are looking for an Engineering Manager to join the Data Products team at Strava, a team at the core of Strava’ AI strategy, responsible for turning Strava's unique community and activity data into reliable, reusable, enriched datasets powering user experiences at scale. This is a technical management role leading a growing team of Machine Learning Engineers, Data Engineers and Data Scientists. You'll be responsible for hands-on technical contributions, driving execution and setting technical strategy as well as coaching and growth of your team. You’ll balance innovative machine learning models with product impact via iterative development to translate durable, high-quality capabilities into athlete experiences at scale across our many product verticals. We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco office — three days per week. WHAT YOU’LL DO: - Build for a Well Loved Consumer Product: Work at the intersection of fitness and geospatial to launch and optimize product experiences that will be used by tens of millions of active people worldwide. Contribute hands on to the solutions we deliver in product. - Lead a High-Impact Data + ML Team: Manage, mentor, and grow a team of machine learning engineers, data engineers and data scientists to deliver ML and data -powered experiences to users while fostering a collaborative culture across experi

Requirements

Department: Department; Team: Engineering