Strava
Consumer Product
EngineeringManager,MLandDataProducts
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“Engineering Manager, ML and Data Products at Strava. Skills: Machine Learning, Data Products, Team Management, Production ML. Build for a Well Loved Consumer Product. Lead a High-Impact Data + ML Team”
What You'll Achieve.
deliver ML and data -powered experiences to users; translate durable, high-quality capabilities into athlete experiences at scale; product impact via iterative development; impact of the systems you build; business outcomes they enable; multiply the output of the broader team
Industry & Context.
solving complex, ambiguous machine learning problems; broken them down into strategies and tactical execution
What They're Looking For.
Must Have
2 years of experience managing an AI/ML engineering team, Demonstrated track record of solving complex, ambiguous machine learning problems, Technical experience building, shipping, and supporting complex ML models in production at scale, Experience building and maintaining production data pipelines and batch/stream workflows, Hands on coding for model development and serving in backend service development on cloud environments, Excellent communication and collaboration skills
Nice to Have
Kubernetes a plus
What You'll Do.
Build for a Well Loved Consumer Product
Lead a High-Impact Data + ML Team
Own End-to-End Data Products Strategy and Execution
Drive the roadmap for Data Products
Guide your team in designing and developing novel models
Build from a rich dataset
Unlock your curiosity and explore datasets
How You'll Work.
Team & Collaboration
Manage, mentor, and grow a team; fostering a collaborative culture; Building cross-functional partnerships; Develop relationships and effectively communicate with many cross-functional partners; Collaborating Across Disciplines; Working fluidly with ML engineers, data engineers, data scientists, and product managers
Communication Scope
Excellent communication and collaboration skills; ability to influence and align stakeholders
Process & Methodology
driving execution, setting technical strategy, iterative development, tactical execution
Full Job Description
ABOUT STRAVA Strava is the app for active people. With over 180 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
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