Senior Machine Learning Engineer, WHOOP
Health
Wearable health and fitness devices
Open for applications
Wearable health and fitness devices
1001+ employees
Open for applications
1001+ employees
Company mission
To unlock human performance and Healthspan.
Role
Who you are
- 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
- The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office
What the job involves
- The 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
- As a 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
- 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
Our take
WHOOP develops wearable health-tracking devices designed to help athletes optimise their performance. Its technology continuously monitors recovery, sleep, and training hours to fine-tune both individual and team performance. Unlike competitors that primarily track exercise data, WHOOP's holistic approach includes metrics like heart rate variability, which can influence more effective and healthier exercise routines.
By focusing on a subscription model that includes the cost of the physical device, WHOOP differentiates itself from competitors that charge a higher one-time fee for their products. This model provides ongoing value and encourages users to stay engaged with their health data.
WHOOP's comprehensive monitoring of strain and recovery has given it a competitive edge, even as other brands like Fitbit have incorporated similar features. Beyond sports performance, WHOOP has conducted extensive research on predicting premature births, aiming to integrate these findings into their app. This commitment to broader health applications demonstrates WHOOP's dedication to advancing wearable health technology.
Steph
Company Specialist at Welcome to the Jungle
Insights
1% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Aug 2021
$200m
SERIES F
Oct 2020
$100m
SERIES E
Total funding: $404.8m
Company benefits
- Flexible Vacation: WHOOP has a flexible vacation policy that allows you to unwind, laptop-free, when you need it most.
- Focus on Family: We offer 18 weeks paid parental leave, plus an additional 2 weeks to gradually return to work.
- Get Invested: In addition to a competitive base salary and 401k, you're eligible to receive stock options to share in the future of WHOOP.
- WHOOP +1: Everyone on the team gets a complimentary WHOOP membership—plus another membership to share with a loved one.
- Health Matters: Our competitive benefits package covers medical, dental, and vision, in addition to mental health services, life and disability insurance, and more.
- Find Your Fit: Full-time employees get $500 a year to spend on wellness in whatever way they see fit, from fitness classes and memberships, to recovery services.
- It Pays to Sleep: Our Sleep Performance Program incentivizes employees to get more sleep. Log an average sleep performance of 85% or higher for the month and get a $100 bonus.
- Location, Location, Location: You can’t beat the views from the rooftop of One Kenmore Square. Feel inspired daily as you work, enjoy free snacks and coffee, and collaborate in the heart of Boston.
Company HQ
West Fens, Boston, MA
Leadership
Will Ahmed
(Founder & CEO)After graduating from Harvard with a Bachelor of Arts in Government and Economics, Will went on to hold Summer Analyst roles at Allen & Company and Lindsay Goldberg before founding WHOOP in 2012.
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