Senior Machine Learning Engineer, Health

Whoop!

Senior Machine Learning Engineer on the Health team at WHOOP, designing and building production ML systems for health metrics analysis. Collaborating with cross-functional teams to improve member health outcomes.

Posted 7/6/2026full-timeBoston • Massachusetts • 🇺🇸 United StatesSenior💰 $150,000 - $210,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudGoogle Cloud PlatformPython

About the role

Key responsibilities & impact

Create, improve, and maintain production services that provide analysis for health features in collaboration with Data Scientists and MLOps Engineers
Collaborate with Data Engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance.
Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency.
Collaborate with researchers and product teams to align model development with health insights and member impact.
Participate in on-call rotations for data science services, ensuring uptime and performance in production environments.

Requirements

What you’ll need

Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related field (Master’s preferred).
4+ years of professional experience as a Machine Learning Engineer or Software Engineer building production ML-enabled systems.
Proven experience working with time series data (wearable/physiological/high-frequency sensor data preferred).
Experience designing, deploying, and operating ML inference systems at scale (real-time streaming and/or large-scale batch).
Strong coding skills in Python with a track record of writing clean, well-tested, production-quality code.
Strong fundamentals in backend/service development (APIs, reliability, monitoring, debugging) as it relates to serving ML models.
Experience deploying and maintaining ML systems on cloud platforms (AWS or GCP), including CI/CD and observability practices.
Familiarity with applied ML development (frameworks, evaluation criteria, performance validation) and translating prototypes into production systems.

Benefits

Comp & perks

benefits and a generous equity package

ATS Keywords

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Hard Skills & Tools

Machine Learning EngineeringProduction ML SystemsPython ProgrammingBackend DevelopmentML Inference SystemsTime Series Data AnalysisCI/CD PracticesObservability PracticesAPIs DevelopmentPerformance Validation

Soft Skills

CollaborationProblem-SolvingCommunication