Principal AI/ML Researcher
At a glance
Senior AI Research role at Whoop. Boston · full-time · $270,000–$300,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Set model architecture across wearable signals, text, biomarkers, and behavior, owning the hardest-to-reverse technical choices
- Choose promising self-supervised and representation-learning research, then take uncertain ideas through validation into production
- Shape AI platform, compute, and infrastructure decisions as part of the team’s broader technical direction
- Connect research, product, and engineering work so technical advances lead to product and business outcomes
- Develop senior technical staff, improve design reviews and evaluation practices, and represent the work in the research community
What you bring
- An advanced degree or equivalent depth, backed by extensive work in large-scale machine learning and AI research
- A record of setting technical direction and making architectural choices with lasting impact beyond a single project
- Deep knowledge of transformers, state space models, multimodal training, self-supervised learning, and distributed training
- Experience taking uncertain research from initial thesis to production, and stopping efforts that lack promise
- Technical leadership demonstrated through team impact, strong communication, and publications at leading machine-learning venues
Who this fits
This role suits a senior research leader who wants to own foundational modeling decisions and turn ambitious research into production capabilities. The position is based in Boston, with relocation required if needed to work from the office. The stated base salary range is $270,000 to $300,000 per year.
From the employer
At WHOOP, we're on a mission to unlock and inspire performance for life. 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 Principal AI Researcher to join our Foundation AI team. This team builds the 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 be one of the senior technical leaders at WHOOP. You will own the technical execution of our foundation modeling workstreams and your technical judgment will shape a core part of WHOOP’s AI efforts and the products they power.
RESPONSIBILITIES:
Set the architectural direction for the development of large-scale models spanning wearable sensor data, text, biomarkers, and behavioral signals, and personally own the highest-stakes, hardest-to-reverse design decisions.
Identify which research bets in self-supervised and representation learning are worth making, and drive the most ambiguous and unproven ones from thesis to validated, production capability.
Contribute to the broader AI strategy and standards at WHOOP, shaping the platform, compute, and infrastructure choices the team operates on, not just working within them.
Partner across research, product, and engineering to connect technical breakthroughs to product and business outcomes.
Raise the technical bar across the team: grow staff and senior engineers, strengthen design-review and evaluation norms, and act as a force multiplier.
Represent WHOOP's technical work externally, helping with recruiting, partnerships, and visibility in the broader AI research community.
QUALIFICATIONS:
Advanced degree (Master’s or Ph.D.) or equivalent depth, with extensive experience in large-scale machine learning and AI research.
A track record of owning technical direction for a significant area and making architectural decisions whose impact outlived any single project.
Demonstrated ability to take ambiguous, high-risk research directions all the way to production impact and the judgment to discontinue those that will not.
Deep expertise in modern deep learning (transformers, state space models), multimodal training, self-supervised and representation learning, RL-based post-training (PPO/DPO/GRPO), and large-scale distributed training (data, model, and context parallelism).
A history of being a technical authority that teams defer to, and evidence of multiplying their output.
Excellent communication and the ability to influence both the engineering bench and senior leadership.
Publications and evidence of community building at top-tier machine learning venues.
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, 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 $270,000 - $300,000. 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.