Drive key projects to power AI/ML platform at Strava end-to-end from gathering stakeholders needs, to ground up development, then following through with adoption and improvements
Help build tooling to leverage Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features
Work at the intersection of AI and fitness to help launch and maintain product experiences that will be used by tens of millions of active people worldwide
Requirements
Have worked on platform level problems, developing tools and systems to address user challenges.
Have demonstrated solid interpersonal and communication skills, and collaborative approach to drive business impact across teams.
Have worked with a variety of generative AI technologies (like LangChain, MCP servers, evaluation frameworks, vector stores)
Have worked with a variety of MLOps tools that fulfill different ML needs (like FastAPI, MLflow, Kubeflow, Feast)
Have experience building, shipping, and supporting software in production at scale in cloud environments (like AWS)
Familiar with data munging through various data technologies (like Pandas, Spark, Airflow, SQL, Snowflake)
Familiar with some production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing