3 months ago
Base Salary
$150k - $210k/yr
Responsibilities
- Create, improve, and maintain production services for core health and fitness features with applied ML scientists and MLOps engineers.
- Improve ML data pipelines, tooling, validation systems, and operational infrastructure for robust model performance.
- Translate research prototypes into scalable production ML systems optimized for latency and cost.
- Collaborate with researchers and Product teams to align model development with physiological insights and member impact.
- Develop observability, alerting, monitoring, performance validation, and incident-response processes, including on-call rotations.
- Mentor engineers and applied ML scientists and contribute to code and system design reviews.
Requirements
- Bachelor’s degree in Computer Science, Data Science, Applied Mathematics, or a related field; a master’s degree is preferred.
- At least 4 years of professional experience as an ML engineer, applied researcher, or software engineer focused on ML systems.
- Experience working with time-series data, including wearable, physiological, or high-frequency sensor data.
- Strong Python coding skills and experience writing clean, production-quality code.
- Experience designing, deploying, and operating production-scale ML systems for millions of users, real-time streaming, or large-scale batch workloads.
- Experience deploying and maintaining ML backend services with APIs, reliability, observability, and monitoring using AWS or GCP.
- Preferred: at least 2 years applying advanced mathematical and statistical techniques.
Benefits
- Full-time position with a U.S. base salary range of $150,000-$210,000, plus equity and benefits.
- Equity package aligned with the company’s long-term growth.
- Role is based in WHOOP’s Boston, Massachusetts office, and the successful candidate must relocate if necessary to work from the office.
- WHOOP is an equal opportunity employer and participates in E-Verify.
Tech Stack
Categories
About WHOOP
WHOOP builds a wearable health and performance tracker paired with an analytics app that measures sleep, recovery, and strain for athletes and health‑conscious consumers. Its business model combines device sales with a recurring membership that unlocks coaching features and insights. Founded in 2012 and headquartered in Boston, the privately held company also serves enterprise wellness programs and sports organizations seeking continuous performance monitoring.