Strava is looking to build and productionalize machine learning models and AI systems that power key Strava user experiences, providing value to athletes across product surfaces with capabilities ranging from personalization, recommendations, search, and trust and safety.
Requirements
- 3+ years of experience managing an AI/ML engineering team, with a proven track record of growing engineers and delivering complex technical projects.
- Focus on applied ML solutions anchored user problems and business goals.
- Demonstrated track record of solving complex, ambiguous machine learning problems and broken them down into strategies and tactical execution
- Technical Experience building, shipping, and supporting ML models in production at scale for domains like recommendation systems, personalization or user understanding.
- Interested in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing, and scalable ML architecture.
Responsibilities
- Build for a Well Loved Consumer Product: Work at the intersection of AI and fitness to launch and optimize product experiences that will be used by tens of millions of active people worldwide
- Lead a High-Impact ML Team: Manage, mentor, and grow a team of machine learning engineers to deliver AI-powered experiences to users while fostering a collaborative culture across experience levels
- Own End-to-End ML Strategy and Execution: Drive the roadmap for ML systems across Strava's platform, from initial model prototyping to production deployment, scaling, and optimization
- Shape AI at Strava: Be a strategic voice in defining Strava's AI vision, leading cross-functional initiatives with Product and Engineering teams to deploy solutions across multiple product surfaces
- Drive Innovation in AI for Fitness: Guide your team in designing and developing novel models and methodologies for unique fitness challenges, including recommendation systems, activity prediction, and personalized athlete insights
- Building cross-functional partnerships: Develop strong relationships and effectively communicate with many cross-functional partners to identify highest leverage opportunities across product verticals
- Championing team culture: Be passionate about developing your people and contributing positively to Strava's inclusive and collaborative culture, fostering an environment where your team can do their best work
Other
- 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
- Excellent communication and collaboration skills, with the ability to influence and align stakeholders across multiple engineering and product teams.
- Strava is an equal opportunity employer.
- We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment.
