Senior Applied Machine Learning Engineer

• 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
• Own End to End AI Systems: Drive key projects powered by ML on the Strava platform end-to-end, from initial model prototyping to shipping production code to scaling and optimizing inference and deployment
• Shape AI at Strava: Be a strong voice on a highly collaborative team with a range of experience levels. Work across teams to deploy ML solutions in multiple surfaces and build out our technical ML capabilities
• Integrate and Collaborate with Product, Design, Client and Server engineers: Be excited about the impact and build Applied ML solutions anchored on the user experience
• Innovate in AI for Fitness: Design and develop novel models and methodologies to take on novel problems that improve athlete experience, including mapping, routing, search and more
• Build from a rich dataset: Explore and use Strava’s extensive unique fitness and geo datasets from millions of users to extract actionable insights, inform product decisions, and optimize existing features

• Have worked on numerous machine learning problems and broken them down into incremental tasks
• Have demonstrated solid interpersonal and communication skills, and collaborative approach to drive business impact across teams
• Have experience building, shipping, and supporting ML models in production at scale
• Have experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, Tensorflow, Sagemaker
• Have built and worked on data pipelines using large scale data technologies (like Spark, Hadoop, EMR, SQL, Snowflake)
• Are experienced and interested in production ML model operational excellence and best practices, like automated model retraining, performance monitoring, feature logging, A/B testing
• Have built backend production services on cloud environments like AWS, using languages like (but not limited to) Python, Scala, Go

Have experience with geospatial data or specifically geospatial ML

Offers Equity