Senior Engineering Manager, Applied Machine Learning

Strava • San Francisco, CA

101d • $260,000 - $310,000

About The Position

Strava is the app for active people. With over 150 million athletes in more than 185 countries, Strava is where connection, motivation, and personal bests thrive. No matter your activity, gear, or goals, we help you find your crew, crush your milestones, and keep moving forward. Start your journey 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 a Senior Engineering Manager to lead our Applied AI and Machine Learning team at Strava. This team is responsible for building and productionalizing machine learning models and AI systems that power key Strava user experiences. These models provide value to our athletes across product surfaces with capabilities ranging from personalization, recommendations, search, and trust and safety. This is a critical leadership role where you'll manage and grow a team of ML engineers. You'll be responsible for roadmapping, driving technical strategy for AI that support Strava across multiple product verticals and balancing innovative machine learning models with product impact from AI solutions at scale. 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.

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.
• 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 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

Benefits

• Compensation: $260,000-$310,000. This range reflects base compensation only and does not include equity or benefits.
• For more information on benefits, please click here.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 251-500 employees