Staff AI/ML Researcher (Foundation AI)
Top focus
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 Staff AI/ML 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 staff 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.
- Serve as a technical mentor for other data scientists, sharing best practices in deep learning, large-scale training, and multimodal data integration.
- 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
- equivalent professional experience. 7+ years of experience in applied ML, AI research
- 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).
- Experience building and scaling large datasets and training large models in 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 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
- retain exceptional talent by offering competitive base salaries, meaningful equity
- consistent pay practices that reflect our mission and core values.
- At WHOOP, we view total compensation as the combination of base salary, equity
- 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 $215,000 - $260,000.
- 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.