Whoop

Senior Machine Learning Engineer, Health

Boston, Massachusetts, U.S.

Full-Time

$150,000 – $210,000 per year

TLDR

Design, build, and productionize ML systems delivering personalized health metrics to millions, at the intersection of data science, backend engineering, and cloud infrastructure.

WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance. WHOOP empowers its members to improve their health and perform at a higher level by providing a deep understanding of their bodies and daily lives. The Health team is responsible for developing novel algorithms and features that expand our health sensing capabilities. Our work spans several key areas, including women’s health, software as a medical device, wellness monitoring, longevity research, and emerging health insights. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. As a SeniorMachine Learning Engineer on our Health team, you will design, build, and productionize ML systems that deliver meaningful, personalized health metrics to millions of members. You will work at the intersection of data science, backend engineering, and cloud infrastructure—deploying robust, scalable, and reliable ML solutions built on physiological and behavioral data streams. This role emphasizes strong coding skills, system design, and the ability to deliver production-ready ML services. Responsibilities

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.

Qualifications

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.

Preferred

Experience developing ML-enabled software in a regulated or quality-managed environment (e.g., QMS-controlled development for SaMD/medical devices), including documentation, traceability, validation/verification practices, and change control.

Demonstrated technical leadership through architecture/design ownership, setting engineering standards, and raising quality via reviews and mentorship.
Proven track record driving measurable improvements in system performance, reliability, and/or cost at scale, and influencing cross-functional technical direction.

This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.

Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.

WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.

The U.S. base salary range for this full-time position is $150,000-$210,000. Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.

In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.

These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.

Benefits

Equity Compensation

generous equity package

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Whoop

Whoop builds a performance optimization platform that helps individuals understand their bodies and health through advanced wearable technology. Targeted at fitness enthusiasts and health-conscious individuals, this startup stands out by focusing on personalized metrics and insights that drive improved performance and longevity.

Founded: Founded 2007
Employees: 51-200 employees
Industry: Internet Software & Services

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Senior Machine Learning Engineer