Senior Machine Learning Engineer, Insights

Whoop; Boston (MA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Benefits package

Equity

Job summary

WHOOP Health Insights seeks a Senior ML Engineer in Boston to develop production ML systems that deliver personalized health metrics for millions of members.

You will work at the intersection of data science, backend engineering, and health research, focusing on robust, scalable ML services and reliable production pipelines.

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 ML engineer, applied researcher, or software engineer with a focus on ML systems.
• Strong coding skills in Python with a track record of writing clean, production-quality code.
• Experience designing, deploying and operating ML inference systems at scale (real-time streaming and/or large-scale batch).
• Strong fundamentals in backend/service development (APIs, reliability, monitoring, debugging).
• 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: 2+ years of experience applying advanced mathematical and statistical techniques.
• Preferred: Experience working with time series data (wearable, physiological, or high-frequency sensor data).

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 physiological insights and member impact
• Participate in on‑call rotations for data science services, ensuring uptime and performance in production environments

Skills

Python

ML systems

APIs

AWS

GCP

CI/CD

Time series data

Education

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

Master’s degree preferred

Tools

AWS

GCP

CI/CD

Kubernetes

Python environments

Job description

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 Insights 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.

As a Senior Machine Learning Engineer on our Health Insights team, you will help develop and deploy machine learning systems that deliver meaningful, personalized health metrics to millions of members. You will work at the intersection of data science, backend engineering, and health research, contributing to scalable ML solutions built on physiological and behavioral data streams. This role emphasizes robust system design, performance, and reliability in production.

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 physiological 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 ML engineer, applied researcher, or software engineer with a focus on ML systems
• Strong coding skills in Python with a track record of writing clean, production‑quality code
• Experience designing, deploying and operating ML inference systems at scale (real‑time streaming and/or large‑scale batch)
• 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: 2+ years of experience applying advanced mathematical and statistical techniques
• Preferred: Experience working with time series data (wearable, physiological, or high‑frequency sensor data)

Location

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.

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.

Learn more about WHOOP.