Senior Machine Learning Scientist (Sensor Intelligence) Sensor Intelligence Boston, MA Boston, MA At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is seeking a Senior Machine Learning Scientist to join the Sensor Intelligence Group (SIG), a cross-functional team collaborating across WHOOP Labs, Firmware, and Data Science. This role is central to developing and scaling machine learning systems that power the most foundational health features at WHOOP. You’ll enable next-generation AI coaching at Whoop, developing robust algorithms for constrained edge and cloud environments,ultimately delivering meaningful and personalized coaching to millions of members. At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. WHOOP is seeking a Senior Machine Learning Scientist to join the Sensor Intelligence Group (SIG), a cross-functional team collaborating across WHOOP Labs, Firmware, and Data Science. This role is central to developing and scaling machine learning systems that power the most foundational health features at WHOOP. You’ll enable next-generation AI coaching at Whoop, developing robust algorithms for constrained edge and cloud environments,ultimately delivering meaningful and personalized coaching to millions of members. 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 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 $150,000 - $215,000 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. RESPONSIBILITIES:

Research, architect, and develop ML systems for member coaching distributed between edge hardware and the cloud

Collaborate with machine learning and edge ML engineers to translate prototypes into production

Partner with product and user experience teams to ensure consistent user experience in bandwidth-constrained environments and to align with member impact and health insights goals

Contribute to architectural decisions and mentor team members in ML best practices

QUALIFICATIONS:

Bachelor's degree in Computer Science, Electrical/Computer Engineering, Applied Mathematics, or a related field; Master’s or PhD degree preferred

5+ years of experience as a Machine Learning Scientist or similar role with a focus on applied research, preferably related to voice and/or text-based conversational systems

Experience training, fine-tuning, and deploying state-of-the-art deep learning architectures to production

Experience with time-series foundation models and self-supervised training approaches

Experience pre-training and fine-tuning small language models and/or building natural language understanding (NLU) models than run on resource-constrained targets

Experience with cloud platforms (AWS or GCP) and familiarity with modern MLOps practices such as CI/CD, model versioning, monitoring, and observability

Strong communication and collaboration skills across cross-functional teams

Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions

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