Software Engineering Manager (AI Quality)

At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers users to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable device tracks key physiological metrics such as heart rate variability, resting heart rate, and sleep quality to provide personalized insights into fitness, health, and recovery.

The AI Quality team at WHOOP is responsible for ensuring the reliability, performance, and integrity of the AI models that power these insights, delivering cutting-edge AI technologies that our members can trust.

As an Engineering Manager at WHOOP, you will have both technical and people management responsibilities. On the technical side, you will partner with product and engineering leaders to uphold our "Measure What Matters" principle, ensuring every AI initiative has clear, visible, and actionable metrics. You will guide a team of AI and ML engineers in developing robust technical designs, architecture, and operational excellence. You will embody our "Decisions Over Consensus" principle, providing clear technical direction and documenting the rationale for high-stakes AI architecture choices.

On the people management side, you will foster a culture of innovation, teamwork, psychological safety, and continuous learning, ensuring all team members feel empowered to do their best work.

RESPONSIBILITIES:

• Lead and manage a team of cross-skilled engineers responsible for measuring and improving the quality of AI outputs.
• Champion the "Measure What Matters" principle by establishing rigorous testing frameworks to evaluate model drift and performance.
• Exercise "Decisions Over Consensus" to provide clear technical direction and resolve alignment stalls for the team.
• Manage third-party vendor relationships, overseeing both technology integration and partnership performance.
• Define technical strategy, architecture, and design for AI quality.
• Drive continuous improvement initiatives to optimize engineering productivity and quality.
• Provide mentorship and coaching to team members to support their professional growth.

QUALIFICATIONS:

• 5+ years of experience in software engineering, with significant experience building and measuring the quality of AI/ML products.
• Proven experience managing third-party vendor relationships and technology partnerships.
• Strong technical skills in Applied AI, Machine Learning, and software deployment lifecycles.
• Excellent communication, interpersonal, and people management skills.
• Passion for wearable technology and experience thriving in a fast-paced, high-growth environment.
• Experience managing an AI product at scale is a plus.

Learn more about our Software Org and how to be successful in your engineering career at WHOOP via our Career Framework.

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-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.