Strava jobs

Strava, the social fitness platform with 180M+ athletes globally, is hiring a Staff Engineer for its Core Services Platform team to lead technical direction for social features like feeds and photo/video sharing. You'll set the technical roadmap, mentor a small engineering pod, drive modernization of critical services, and partner with product teams—working across Ruby, Scala, Go, MySQL, Redis, Cassandra, Kafka, and Kubernetes. The role requires 10+ years of backend engineering with a proven track record leading technical projects and serving as a tech lead, plus strong distributed systems design skills and proficiency in at least one of Strava's backend languages. The position is hybrid in San Francisco or Denver (three days on-site weekly) and backed by top-tier investors including Sequoia Capital. A notable bonus is experience with feed systems, social graphs, or large-scale migrations—though not required—and this is a genuinely technical leadership role, not a people-management track, focused on owning architectural vision rather than headcount.

This is a Senior Backend Engineer role on Strava's Subscriptions Team, responsible for designing and maintaining scalable backend services that power the company's subscription and payments platform. You'll develop APIs, collaborate across product and engineering teams, mentor other engineers, and help shape the technical future of payments infrastructure at Strava. The role requires 7+ years of backend software development experience, proficiency in at least one of their core languages (Ruby, Java, Scala, Python, or Go), and solid experience with relational and NoSQL databases, distributed systems (Kafka, Kubernetes, Docker), and ideally subscription or payments infrastructure. Strava is a well-funded fitness community app with 180+ million athletes globally, backed by top-tier VCs including Sequoia Capital. The position is hybrid in San Francisco with a requirement to be on-site at least three days per week—notably more structured than typical tech flexibility.

Strava is hiring a Senior Engineer for its Foundation engineering team, which builds the core platform infrastructure supporting the app's 180+ million athletes. You'll develop and maintain shared platform tools, frameworks, and CI/CD pipelines across multiple languages and runtimes while improving developer velocity and workflows. Required qualifications include a solid foundation in software engineering, comfort with polyglot environments (Go, Python, JavaScript, Scala), and hands-on experience designing and operating distributed microservices in containerized cloud environments like Kubernetes. Notably, Strava is backed by top-tier VCs (Sequoia, TCV) and operates on a flexible hybrid model requiring three days per week in their San Francisco office. The role emphasizes mentorship and end-to-end project ownership with minimal supervision, making it ideal for a senior engineer ready to shape developer experience across the company.

Strava is seeking a Machine Learning Engineer to join its AI/ML team, which builds recommendation systems, personalization, search, and trust & safety features used by 180+ million athletes globally. You'll own end-to-end ML projects from prototyping through production deployment, working with Strava's unique fitness and geolocation datasets to solve novel problems in activity prediction and personalized insights. Required experience includes shipping production ML models at scale, proficiency in Python/R with libraries like PyTorch and TensorFlow, building data pipelines with Spark/Snowflake/SQL, and backend services on AWS using Python, Java, Go, or similar languages; you should also have solid understanding of ML ops best practices like automated retraining and A/B testing. The role is based in San Francisco with a hybrid schedule requiring three days per week on-site, and you'll work cross-functionally with product managers, data scientists, and engineers to drive business impact. Strava is well-funded by top-tier VCs (Sequoia, TCV) and backed by a passionate community of athletes, offering the chance to shape AI capabilities for a consumer product used by tens of millions.