Machine Learning Engineer

Role Overview

Join Strava as a Machine Learning Engineer (full remote). You’ll build and optimize machine learning models and systems that drive value for Strava athletes, partnering with cross-functional teams to move ideas from prototype to production.

Key Missions

• Contribute to ML-driven projects, from initial model prototyping to shipping production code.
• Collaborate with cross-functional partners and product teams to identify opportunities and deliver the team’s technical vision.
• Apply best practices for ML development, deployment, and maintenance, ensuring high quality throughout the lifecycle.

Responsibilities

• Build, ship, and support ML models in production at scale.
• Maintain the ML platform and infrastructure.
• Maintain production ML operational excellence (e.g., retraining and monitoring) and deliver continuous improvements.

Requirements

• Strong interpersonal and communication skills; ability to collaborate across teams.
• Experience building backend production services on cloud environments such as AWS using languages including (but not limited to) Python, Ruby, Java, Scala, or Go.
• Experience with production ML model delivery and support at scale.
• Experience building data pipelines with large-scale technologies such as Spark, Hadoop, EMR, SQL, and Snowflake.
• Experience with exploratory data analysis (EDA) and model prototyping using tools/languages such as Python or R, and scikit-learn, Pandas, NumPy, PyTorch, TensorFlow, and SageMaker.
• Experience on impactful ML problems with incremental progress toward long-term goals.
• Interest in production ML operational excellence, including automated model retraining, performance monitoring, feature logging, and A/B testing.

Nice-to-haves

• Not explicitly stated.