--- title: 'Senior AI/ML Researcher (Foundation AI) at Whoop' canonical: 'https://feeny.ai/job/senior-ai-ml-researcher-foundation-ai-whoop-boston-s6hyn18f6zw5' type: 'job' last_seen: '2026-10-14' --- # Senior AI/ML Researcher (Foundation AI) at Whoop - **Company:** [Whoop](https://feeny.ai/companies/whoop) - **Location:** Boston, MA - **Compensation:** $190k–$230k - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-07-10 - **Last confirmed live:** 2026-10-14 - **Apply:** https://jobs.ashbyhq.com/whoop/85da87ff-c1a6-4fcd-8c7c-162e57b18281/application **Skills:** Python, PyTorch, TensorFlow, Transformers, State space models, Multimodal model training, Distributed training, Multi-node compute, Multi-GPU compute, Data parallelism, Model parallelism, Context parallelism, Representation learning, Self-supervised learning, Reinforcement learning, PPO, DPO, GRPO, MLOps, Model versioning > WHOOP is seeking a Senior AI Researcher to design, train, and deploy large-scale multimodal foundation models. The role involves applied research in self-supervised learning and distributed training, collaborating with cross-functional teams to deliver intelligent health-enhancing experiences. ## Job description WHOOP is an advanced health and fitness wearable on a mission to unlock human performance and extend healthspan. By providing members with a deep understanding of their bodies, behaviors, and daily lives, WHOOP empowers healthier choices and peak performance. We are seeking a Senior AI Researcher to join our Foundation AI team. This team builds the multimodal foundation models that underpin WHOOP’s next generation of intelligent, personalized, and health-enhancing experiences. These models integrate data across wearable sensors, language, biomarkers, clinical information, and self-reported inputs to create scalable AI systems that understand human physiology and behavior. In this role, you’ll serve as a senior individual contributor driving the research, development, and deployment of large-scale multimodal models. You’ll collaborate closely with data scientists, ML engineers, and cross-functional partners to push the boundaries of deep learning and ensure our models deliver measurable value to WHOOP members. ## RESPONSIBILITIES: - Design, train, and optimize large-scale multimodal foundation models that integrate wearable sensor data, text, biomarkers, and behavioral data. - Conduct applied research in self-supervised learning, representation learning, and downstream task fine tuning to advance WHOOP’s core model capabilities. - Develop scalable, distributed training pipelines for large models on high-performance compute environments. - Collaborate with MLOps, data engineering, and software engineering teams to operationalize models for production deployment, ensuring robustness, reproducibility, and observability. - Partner with product and research teams to translate foundation model capabilities into downstream features that deliver meaningful member value. - Contribute to the technical roadmap and architectural direction for foundation model development at WHOOP. - Ensure models adhere to WHOOP’s standards for ethical, transparent, and privacy-preserving AI. ## QUALIFICATIONS: - Advanced degree (Master’s or Ph.D.) in Computer Science, Machine Learning, Electrical Engineering, or a related field, or equivalent professional experience. - 7+ years of experience in applied ML, AI research, or large-scale modeling, with a track record of delivering production systems. - Expertise in modern deep learning (e.g., transformers, state space models), multimodal model training. - Proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow). - Familiarity with training models on  mulit-node, multi-gpu distributed compute environments. - Familiarity with best practices for data, model, and context parallelisms. - Strong applied experience with representation learning, self-supervised methods, and post-training for downstream applications. - Experience with reinforcement learning for post-training foundation models (PPO, DPO, GRPO etc.). - Familiarity with MLOps best practices including model versioning, evaluation, CI/CD for ML, and cloud-based compute. - Excellent communication skills and ability to collaborate cross-functionally with engineers, researchers, and product teams. - Passion for WHOOP’s mission to improve human performance and extend healthspan through science and technology. 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. The WHOOP compensation philosophy is designed to attract, motivate, and retain exceptional talent by offering competitive base salaries, meaningful equity, and consistent pay practices that reflect our mission and core values. 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 $190,000 - $230,000. 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. ## 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. 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