---
title: 'Senior Machine Learning Engineer, Core Algorithms at Whoop'
canonical: 'https://feeny.ai/job/senior-machine-learning-engineer-core-algorithms-whoop-boston-v7pp734hn501'
type: 'job'
last_seen: '2026-10-14'
---

# Senior Machine Learning Engineer, Core Algorithms at Whoop

- **Company:** [Whoop](https://feeny.ai/companies/whoop)
- **Location:** Boston, MA
- **Compensation:** $150k–$210k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-07-15
- **Last confirmed live:** 2026-10-14
- **Apply:** https://jobs.ashbyhq.com/whoop/5502fb12-e948-4f62-8db6-b725fb3dc8e5/application

**Skills:** Python, ML inference systems, APIs, AWS, GCP, CI/CD, Observability, Real-time streaming, Large-scale batch processing, Time series data, Advanced mathematical techniques, Statistical techniques, Wearable data, Physiological data, High-frequency sensor data

> Design, build, and productionize ML systems to deliver personalized health metrics. Collaborate with data scientists and engineers to translate research prototypes into scalable, production-ready ML solutions focused on physiological data.

## 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.

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.

Responsibilities:

- 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.

Qualifications:

- 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.
- Experience working with time series data (wearable, physiological, or high-frequency sensor data).
- Strong coding skills in Python with a track record of writing clean, production-quality code.
- Experience designing, deploying and operating ML production systems at production scale (millions of users, real-time streaming and/or large-scale batch).
- Experience deploying and maintaining ML backend services (APIs, reliability, observability, monitoring; AWS or GCP).
- Preferred: 2+ years experience applying advanced mathematical and statistical techniques.

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.

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.

WHOOP is an Equal Opportunity Employer and participates in [E-verify](https://www.e-verify.gov/) 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.

At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.

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](https://www.whoop.com/us/en/careers/?srsltid=AfmBOopKmph9d0DLBlogZu8mx6do0dzjNS8eJlfc4PQqQtdU6F8DGKBg).

## About Whoop

## Company Overview
- **One-liner**: WHOOP is a human performance optimization platform that uses a wearable device and 24/7 monitoring to help members improve sleep, strain, recovery, and overall health.
- **Entity Type**: Private (funding stage not publicly available in provided sources)
- **Headquarters**: Boston, Massachusetts, USA
- **Founded**: 2012
- **Founders**: Will Ahmed

## Core Business
- **Primary industry**: Wearable health technology, human performance optimization
- **Target customers**: B2C (consumers, athletes) and B2B (professional sports teams, organizations)
- **Mission**: “To unlock human performance and Healthspan.” [whoop.com - About](https://www.whoop.com/us/en/about/)

## Products & Services
- **WHOOP 5.0 + Subscription**: A non-screen wrist-worn wearable with 14+ day battery life that continuously monitors sleep, strain, recovery, heart rate, heart rate variability, and 65+ biomarkers. The platform provides personalized coaching, blood pressure insights, women’s hormonal insights, VO₂ max, heart rate zones, and mental health tracking. Type: Hardware + SaaS subscription. [whoop.com - Homepage](https://www.whoop.com/us/en/)

## Market Standing
- **Valuation/Market Cap**: Not publicly available from provided sources
- **Key Metric**: Not publicly available (annual revenue not disclosed); estimated headcount of 500 employees [Built In Boston](https://www.builtinboston.com/company/whoop)
- **Notable Investors/Partners**: Not disclosed in provided sources
- **Growth Signals**: 500 total employees; hybrid workspace (4 days on-site per week); actively hiring across Engineering, AI/ML, Data & Analytics, Product, and Design; only 0.13% of applicants are hired, indicating high selectivity and strong talent demand. [whoop.com - Careers](https://www.whoop.com/us/en/careers/) | [Built In Boston](https://www.builtinboston.com/company/whoop)

## Competitive Advantages
- Proprietary 24/7 physiological monitoring with advanced sensor technology and an ultra-long battery life (14+ days)
- Deep scientific foundation – founded after reviewing over 500 medical papers
- Personalized coaching and insight delivery based on individual biometric data
- Strong brand recognition among elite athletes and mainstream consumers
- Privacy-first design with encrypted data storage [whoop.com - Homepage](https://www.whoop.com/us/en/)

## Strategic Focus
- Expanding health insights: introducing blood pressure monitoring, women’s hormonal health features, and heart health tracking
- Enhancing AI/ML capabilities (evident from many open AI/ML roles) [jobs.lever.co](https://jobs.lever.co/whoop)
- Deepening enterprise/B2B partnerships with sports organizations and research institutions
- Continuing to build out Healthspan and longevity features

## Why Work Here
- **Hybrid workspace** – employees are on-site 4 days a week in Boston’s “best office” [whoop.com - Careers](https://www.whoop.com/us/en/careers/)
- **Benefits** – flexible time off, above-market compensation, paid parental leave, health support [whoop.com - Careers](https://www.whoop.com/us/en/careers/)
- **Employee Resource Groups** – ADAPT (disability inclusion), BLACK@WHOOP, LGBTQ+ (WHOOP GOOP), Veterans and Military Personnel, Women of WHOOP, Women in Science and Engineering, WHOOP Parents [whoop.com - Careers](https://www.whoop.com/us/en/careers/)
- **High selectivity** – only 0.13% of applicants are hired, reflecting a rigorous, standards-driven culture [whoop.com - Careers](https://www.whoop.com/us/en/careers/)
- **Equal Opportunity Employer** – committed to diversity and inclusion in all employment decisions [whoop.com - Careers](https://www.whoop.com/us/en/careers/)

## Sources
1. [whoop.com - Careers](https://www.whoop.com/us/en/careers/)
2. [whoop.com - About](https://www.whoop.com/us/en/about/)
3. [whoop.com - Homepage](https://www.whoop.com/us/en/)
4. [Built In Boston - WHOOP Office Profile](https://www.builtinboston.com/company/whoop)
5. [jobs.lever.co - WHOOP Job Listings](https://jobs.lever.co/whoop)

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