Senior Machine Learning Engineer

About the role

ABOUT STRAVA

Strava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts—it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey https://www.strava.com/subscription with Strava today.

Our mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward.

We are looking for a Machine Learning Engineer to join the growing AI and Machine Learning team at Strava. This team is responsible for sophisticated machine learning models and systems which provide value to Strava athletes including personalization, recommendations, search, and trust and safety. The team also maintains the ML platform and infrastructure that enables our team to iterate on models quickly and deploy them reliably at scale.

This is an important role in the ML team and across Product teams designing, roadmapping, and implementing innovative machine learning algorithms. We value full stack ML engineers who are able to work on all parts of an ML pipeline from model building, evaluation, optimizing performance, and ensuring the scalability and reliability of these production models. We also seek those who can improve the systems and tools behind the ML pipeline to further empower the team.

We follow a flexible hybrid model that translates to more than half your time on-site in our San Francisco Office — three days per week.

WHAT YOU’LL DO:

- 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.

- Innovate in AI for Fitness: Design and develop novel models and methodologies to take on novel problems that improve athlete experience, including recommendation systems, activity prediction, and personalized insights.

- 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

YOU WILL BE SUCCESSFUL HERE BY:

- Driving innovation with Product in mind: Stay up-to-date with the latest research in machine learning, AI, and related fields. Experiment, advocate and get buy-in for innovative techniques to improve existing products or explore new features that result in step function changes to how we build AI at Strava.