Senior Machine Learning Engineer, Core Algorithms

About the Role

WHOOP is an advanced health and fitness wearable on a mission to unlock human performance. Our Machine Learning Core Algorithms team is responsible for developing novel algorithms and features that expand our health and fitness capabilities with wearable sensor data, focusing on performance-related insights for sleep, recovery, and exercise.

As a Senior Machine Learning Engineer on our Core Algorithms team, you will design, build, and productionize ML systems that deliver meaningful, personalized metrics to millions of members. You will work at the intersection of data science, backend engineering, and cloud infrastructure to deploy robust, scalable, and reliable ML solutions built on physiological and behavioral data streams.

Responsibilities

• Create, improve, and maintain production services that provide analysis for core features in collaboration with applied ML scientists and MLOps engineers.
• Improve ML data pipelines, tooling, and validation systems that support robust model performance.
• Work alongside applied ML 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 physiological insights and member impact.
• Build operational maturity across the team by developing processes for observability, alerting, and incident response (including on-call rotations).
• Develop applied ML operational infrastructure (frameworks, evaluation criteria, performance validation).
• Mentor other engineers and applied ML scientists on production practices through code and system design reviews.

Qualifications

• Bachelor’s Degree in Computer Science, Data Science, Applied Mathematics, or a related field (Master’s preferred).
• 4+ years of professional experience as an ML engineer, applied researcher, or software engineer with a focus on ML systems.
• Experience working with time series data (wearable, physiological, or high-frequency sensor data).
• Strong coding skills in Python with a track record of writing clean, production-quality code.
• Experience designing, deploying, and operating ML production systems at scale (millions of users, real-time streaming, and/or large-scale batch).
• Experience deploying and maintaining ML backend services (APIs, reliability, observability, monitoring; AWS or GCP).
• Preferred: 2+ years of experience applying advanced mathematical and statistical techniques.