Engineering Manager, ML and Data Products

Strava • San Francisco, CA

3d • $240,000 - $260,000 • Hybrid

About The Position

Strava is looking for an Engineering Manager to join the Data Products team. This team is central to Strava's AI strategy, focused on transforming community and activity data into reliable, enriched datasets that power user experiences at scale. This is a technical management role leading a team of Machine Learning Engineers, Data Engineers, and Data Scientists. The role involves hands-on technical contributions, driving execution, setting technical strategy, and coaching team members. The manager will balance innovative machine learning models with product impact through iterative development to deliver high-quality capabilities for athlete experiences across various product verticals.

Requirements

• 2 years of experience managing an AI/ML engineering team, with a proven track record of growing engineers and delivering complex technical projects.
• Demonstrated track record of solving complex, ambiguous machine learning problems and breaking them down into strategies and tactical execution for teams.
• Technical experience building, shipping, and supporting complex ML models in production at scale.
• Experience building and maintaining production data pipelines and batch/stream workflows using technologies like Spark, Kafka, Snowflake, or similar.
• Hands-on coding for model development and serving in backend service development on cloud environments (AWS preferred), using Python.
• Interest in production ML model operational excellence and best practices, including scalable ML architecture, serving optimization, and dataset versioning.
• Excellent communication and collaboration skills, with the ability to influence and align stakeholders across multiple engineering and product teams.

Nice To Haves

• Treating Data Products as Products: Bringing engineering rigor (versioning, contracts, SLAs, monitoring, and deprecation paths) to data artifacts and ML insights.
• Leading as an Owner: Taking end-to-end accountability for the reliability and impact of systems, including correctness in production, adoption by downstream teams, and business outcomes.
• Building for Leverage: Designing platforms and tooling that multiply the output of the broader team, reducing ML and data engineering expertise required for CUJ teams.
• Collaborating Across Disciplines: Working fluidly with ML engineers, data engineers, data scientists, and product managers to align on artifact semantics, evaluation standards, and consumption patterns.
• Raising the Standard: Helping establish best practices for data product development, access patterns, and operational health, and mentoring teammates at all levels.
• Being passionate about the work and contributing positively to Strava's inclusive and collaborative team culture and values.

Responsibilities

• Build and optimize product experiences at the intersection of fitness and geospatial data for tens of millions of users worldwide, contributing hands-on to solutions.
• Manage, mentor, and grow a team of machine learning engineers, data engineers, and data scientists, fostering a collaborative culture.
• Drive the roadmap for Data Products, including models, datasets, and systems, from prototyping to production deployment, scaling, and optimization.
• Guide the team in designing and developing novel models, algorithms, and datasets for fitness, routing, and athlete insights.
• Develop strong cross-functional relationships and communicate effectively with product and engineering partners to identify high-leverage opportunities.
• Champion team culture by fostering an environment where the team can do their best work, contributing positively to Strava's inclusive and collaborative culture.
• Explore Strava’s extensive fitness and geo datasets to extract actionable insights, inform product decisions, and optimize existing features.

Benefits

• Flexible hybrid model (more than half time on-site in San Francisco office - three days per week)
• World-class, inclusive workplace
• Opportunities for growth and development

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed