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 Machine Learning and Research. This role focuses on developing compact machine learning models for edge deployment and is central to scaling AI systems that power WHOOP's most foundational health features. In this role, you'll develop next-generation, personalized AI from prototyping to productization, ultimately delivering personalized coaching to millions of WHOOP members.

RESPONSIBILITIES:

• Research, prototype, and productize lightweight deep learning models suitable for resource-constrained edge targets
• Drive deep learning model customization and compression strategies such as distillation, pruning, fine-tuning, and quantization-aware training
• Collaborate with product teams to define member experience targets and with cloud-focused machine learning teams to implement distributed AI systems
• Lead build/buy decisions by evaluating commercial and open-source model performance for WHOOP use cases
• Stay current in Edge AI industry trends and best practices and mentor junior team members

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 advanced development, preferably related to voice and/or text-based conversational systems
• Demonstrated experience training, fine-tuning, and deploying state-of-the-art deep learning architectures to resource-constrained embedded targets

• 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

ADDITIONAL DESIRABLE EXPERIENCE:

• Experience deploying deep learning models to microcontrollers or other resource-constrained edge devices using toolchains such as TFLite/LiteRT or ExecuTorch, and with inference libraries such as CMSIS-NN or CMSIS-DSP
• Experience developing machine learning models for consumer-facing products
• Experience building multi-modal datasets, including speech, video, text, or physiological signals, for human-AI interaction
• Familiarity with time-series foundation models and self-supervised learning methods

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.

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.