Senior Machine Learning Engineer

Strava is the leading digital community for active people, with more than 120 million athletes in more than 190 countries. The platform offers a holistic view of your active lifestyle, no matter where you live, which sport you love, and/or what device you use. Everyone belongs on Strava when they are pursuing an active life.This role is on the AI and Machine Learning team, which is responsible for building ML models that power key product experiences on Strava. These models help enable personalization, recommendation, growth modeling, activity analysis, search, and many other key components of the Strava platform.The AI and ML team is hiring a full-stack ML engineer responsible for working on all parts of the ML pipeline. This includes prototyping and building ML models, deploying models, building production data pipelines, writing server-side production code, and production dev ops.You’re excited about this opportunity because you will:Work at the intersection of AI and fitness to build product experiences that will be used by tens of millions of active people worldwideSpearhead key projects powered by ML on the Strava platform end-to-end, from initial model prototyping to shipping production codeContribute to a highly collaborative team with a range of experience levels.Explore Strava’s extensive dataset to find novel approaches that can be uniquely solved with ML approaches.You will be successful here by:Being passionate about the work you are doing and contributing positively to Strava’s inclusive and collaborative team culture and valuesCollaborating closely with product teams to design, develop, and ship your projectsOwning your work end-to-end and being accountable for the outcomesApplying a growth mindset to constantly be proactive about learning new skillsWorking closely with and helping mentor other ML engineers on the teamWe’re excited about you because you:Have experience building, shipping, and supporting ML models in production at scaleHave experience with exploratory data analysis and model prototyping, using languages such as Python or R and tools like Scikit learn, Pandas, Numpy, Pytorch, SagemakerHave built and worked on data pipelines using big 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 loggingHave built backend cloud-based services in a production environment, using languages like (but not limited to) Ruby, Java, Scala, Python, Go, and tools like AWSStrava is an equal opportunity employer.

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