Head of Applied AI

Whoop
Boston, MA$200k – $300kPosted 27 March 2026

Job Description

Head of Applied AI 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 Head of Applied AI to lead the development and deployment of intelligent systems that power the next generation of the WHOOP experience. This role reports to the SVP of Software. This is a unique opportunity to shape how AI is used to drive health, recovery, and performance outcomes for millions of members globally. In this role, you will define and execute the AI strategy across product, platform, and operations—bringing together cutting-edge models and real-world applications. You’ll lead a multidisciplinary team of researchers, engineers, and data scientists, and serve as a key voice in how WHOOP approaches ethical, scalable, and impactful AI. RESPONSIBILITIES: - - Define and execute WHOOP’s applied AI strategy, integrating internal and external models across features, services, and operations - Lead end-to-end development of AI solutions and features—from early prototyping to deployment and ongoing optimization. - Own the roadmap for our generative AI and agentic platform, ensuring they deliver personalized coaching, insights, and experiences at scale - Partner with Product, Software, Research, and Analytics to ensure AI initiatives align with strategic priorities and deliver measurable impact - Build and develop a high-performing team of AI engineers, software engineers, and data scientists; foster a culture of technical rigor and ownership - Guide architectural decisions, as well as model hosting, deployment, and tuning practices; stay hands-on when needed to drive technical excellence - Ensure model quality, performance, privacy, and compliance with ethical AI principles - Represent WHOOP in academic, industry, and partnership forums to elevate our innovation and attract top-tier AI talent QUALIFICATIONS: - - 10+ years of experience in AI, machine learning, data science, software engineering including 5+ years in a leadership role - Proven success building, leading, and scaling cross-functional AI teams in production environments - Deep technical expertise in generative AI, large language models, and agentic systems, including both open-source and close-source models - Strong experience with the full applied AI lifecycle—including prompt engineering, model experimentation, deployment (MLOps), and fine-tuning, and reinforcement learning - Demonstrated ability to align AI initiatives with business strategy and create measurable value - Excellent communication skills with the ability to influence across technical, executive, and cross-functional audiences - Experience collaborating with Product, Engineering, and Research leaders to deliver integrated solutions - Background in health tech, performance science, or high-complexity domains is a plus - 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 WHOOP is an Equal Opportunity Employer and participates in E-verify https://web.archive.org/web/20230208080845/https://www.e-verify.gov/ to determine employment eligibility. 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. 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-t ... (truncated, view full listing at source)
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