Machine Learning Engineer, WHOOP
Training
$125-170k
+ Equity
More information about location
Wearable health and fitness devices
Be an early applicant
Wearable health and fitness devices
1001+ employees
Be an early applicant
$125-170k
+ Equity
More information about location
1001+ employees
Company mission
To unlock human performance and Healthspan.
Role
Who you are
- Bachelor's Degree in Mathematics, Statistics, Computer Science, or a related field
- 2+ years of ML engineering, applied research, or a similar role
- 2+ years experience applying advanced mathematical and statistical techniques
- Experience deploying and maintaining production ML systems on cloud platforms (e.g., Kubernetes, AWS, GCP)
- Familiarity with MLOps best practices and the ability to collaborate effectively with infrastructure teams on Docker, CI/CD workflows, model versioning, and observability tools
- Preferred experience working with time series data, preferably with wearable data applications
- Proficiency in scientific Python and SQL
- Excellent verbal and written communication skills
- 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
What the job involves
- As a Machine Learning Engineer II on our Training team, you will develop algorithmic features and metrics that capture aspects of daily movement, exercise, and training
- You'll integrate diverse data sources—including WHOOP sensor data and gold-standard reference datasets—while grounding your work in clinical theory and scientific literature
- You’ll work with data from a variety of sources including processed time series data generated by sensors on the WHOOP Strap, data collected from “gold-standard” devices, and data entered manually by WHOOP members via the mobile application
- Using these data sources, as well as drawing upon clinical theory and evidence, you will design, train, and deploy machine learning algorithms to analyze training data
- We’re looking for someone who has experience developing ML models with large datasets in Python and who is excited about the use of wearables in the health and wellness space
- Design, train, and optimize machine learning algorithms for movement, exercise and training applications across diverse backend platforms
- Collaborate closely with data scientists, ML Ops and software engineering teams to ensure reliable deployment, observability, and robust integration with the WHOOP ecosystem
- Contribute to technical roadmap development and architectural decision-making for projects that you are involved in
- Work closely with a team of data scientists in developing algorithms that power member-facing features
- Work with Data Engineers to improve data pipelining, tooling for machine learning, and systems for quality and validation
- Periodically serve as the on-call data scientist to respond in real time to incidents affecting production services
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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