Senior Engineering Manager, Applied Machine Learning at Strava

San Francisco, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Fitness, Technology, SportsIndustries

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 in user problems and business goals
Demonstrated track record of solving complex, ambiguous machine learning problems and breaking 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
Excellent communication and collaboration skills, with the ability to influence and align stakeholders across multiple engineering and product teams

Responsibilities

Build for a well-loved consumer product: Work at the intersection of AI and fitness to launch and optimize product experiences 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 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 the team in designing and developing novel models and methodologies for unique fitness challenges, including recommendation systems, activity prediction, and personalized athlete insights
Build cross-functional partnerships: Develop strong relationships and effectively communicate with cross-functional partners to identify highest leverage opportunities across product verticals
Champion team culture: Be passionate about developing people and contributing positively to Strava's inclusive and collaborative culture, fostering an environment where the team can do their best work

Skills

Machine Learning

Applied AI

ML Engineering

Personalization

Recommendations

Trust and Safety

ML Productionization

Scaling

Deployment

Prototyping

Roadmapping

Technical Strategy

Team Management

Mentoring

Strava

Fitness tracking and social networking platform

About Strava

Strava is a digital platform that allows athletes and fitness enthusiasts to record, track, and analyze their physical activities, offering metrics like speed, pace, and distance. It operates on a freemium model, providing basic services for free while charging for premium features such as advanced training plans and detailed activity breakdowns. Strava distinguishes itself from competitors through its social networking aspect, enabling users to share activities and connect with others, fostering a supportive community. The goal of Strava is to enhance the fitness experience by providing valuable performance insights and encouraging community engagement.

San Francisco, CaliforniaHeadquarters

2009Year Founded

$147.3MTotal Funding

SERIES_FCompany Stage

Consumer Software, Social ImpactIndustries

501-1,000Employees