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

Offers Equity