Senior Machine Learning Engineer (Core Algorithms)

• Our Machine Learning Core Algorithms team is responsible for developing novel algorithms and features that expand our health and fitness capabilities with wearable sensor data. We combine continuous physiological data with clinical research and expert knowledge to generate features that are both scientifically grounded and deeply impactful for members. This role is located on our Core Algorithms team: performance-related insights for sleep, recovery, and exercise
• As a Senior Machine Learning Engineer on our Core Algorithms team, you will design, build, and productionize ML systems that deliver meaningful, personalized metrics to millions of members. You will own the ML systems you build in collaboration with applied machine learning scientists
• 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 systems
• Create, improve, and maintain production services that provide analysis for core features in collaboration with applied ML scientists and MLOps engineers
• Improve ML data pipelines, tooling, and validation systems that support robust model performance
• Work alongside applied ML 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
• Build operational maturity within the Core Algorithms team as well as the broader Machine Learning team, developing processes for observability, alerting, and incident response (including on-call rotations)
• Develop applied ML operational infrastructure (frameworks, evaluation criteria, performance validation)
• Mentor other engineers and applied ML scientists on production practices, raising the bar through code and system design review

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.

Preferred experience

• Experience deploying and maintaining ML backend services (APIs, reliability, observability, monitoring; AWS or GCP)
• Experience working with time series data (wearable, physiological, or high-frequency sensor data)
• Bachelor’s Degree in Computer Science, Data Science, Applied Mathematics, or a related field (Master’s preferred)
• 4+ years of professional experience as an 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
• Preferred: 2+ years experience applying advanced mathematical and statistical techniques
• Experience designing, deploying and operating ML production systems at production scale (millions of users, real-time streaming and/or large-scale batch)
• 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