Senior Machine Learning Engineer (Health)

Mass Digital Health; Boston (MA); On-site; USD 120,000 - 160,000; Full time

Job summary

WHOOP is seeking a Senior Machine Learning Engineer for its Boston office, specializing in developing scalable ML systems that provide personalized health metrics. This role requires collaboration with data scientists and ML engineers and emphasizes strong coding skills in Python and SQL.

The ideal candidate will have significant experience in machine learning, particularly with time series data, and a background in cloud platforms. WHOOP offers an inclusive environment and the possibility of relocation for the right candidate.

Qualifications

• 5+ years of experience focusing on ML systems or Software Engineering.
• Experience in designing and deploying ML inference systems at scale.
• Ability to work with wearable or physiological data.

Responsibilities

• Develop and maintain production services for health features.
• Collaborate with Data Engineers on ML data pipelines.
• Translate research prototypes into production ML systems.

Skills

Machine Learning expertise

Python programming

SQL

Time series data analysis

Cloud platforms (AWS or GCP)

MLOps best practices

Backend service development

Strong communication

Education

Bachelor's Degree in Computer Science, Data Science, or Applied Mathematics

Master's Degree (preferred)

Job description

WHOOP is an advanced health and fitness wearable, on a mission to unlock human performance and healthspan. 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.

Health team is responsible for developing novel algorithms and features that expand our health capabilities. Our work spans several key areas, including women’s health, medical device–grade metrics, 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.

Senior Machine 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.
• 5+ years of professional experience as a Machine Learning Engineer or Software Engineer with focus on ML systems.
• Proven expertise working with time series data (wearable, physiological, or high-frequency sensor data strongly preferred).
• Experience designing and deploying ML inference systems at scale: both real-time streaming and large-scale batch pipelines.
• Strong coding skills in Python (scientific stack) and SQL, with a track record of writing clean, production-quality code.
• Strong communication skills to collaborate across engineering, research, and product teams.
• Proven experience deploying and maintaining ML systems on cloud platforms (AWS or GCP)
• Working familiarity with MLOps best practices: model versioning, CI/CD for ML, observability, and monitoring for inference systems.
• Ability to reason about and design for performance trade-offs (latency vs. throughput vs. cost) when building ML inference systems.
• Strong understanding of backend service development (APIs and service reliability) as it applies to serving ML models at scale.

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.

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.