Senior Product Manager, AI

Whoop•Boston, MA

2d•$155,000 - $215,000•Onsite

About The Position

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. The AI team at WHOOP turns continuous physiological data into recommendations members act on every day. The quality of that intelligence is the product, and as it reaches more members across more surfaces, the work of measuring it, choosing the models behind it, understanding what it costs, and giving the rest of the company the tooling to build on it has grown into a role of its own. WHOOP is hiring a Senior Product Manager to work at that layer, alongside our AI engineers, research scientists, and data scientists. The work spans how AI output quality gets measured and enforced, which models and providers power which experiences, the internal AI platform that teams across WHOOP use to build agents, and which emerging techniques from the research world are worth a bet. This is a platform-oriented AI product role. Your users are as often internal (agent authors, analysts, engineers, research scientists) as they are members. It suits someone technical enough to earn the trust of ML researchers, organized enough to run a program across several teams without direct authority, and disciplined enough to say no to most of what is possible.

Requirements

Experience shipping AI or machine learning products, where the underlying capability was probabilistic rather than deterministic.
Depth in evaluation and measurement: you have defined how something gets measured, not only reported on it.
Working literacy in modern ML: you understand what fine-tuning is and the main flavors of it, what RL-based post-training is for, and how the current generation of techniques fits together. You do not need to implement them, but you should know what they buy you and what they cost.
Experience with platform or internal-facing products, where the users are other teams.
Technical fluency sufficient to partner with research and engineering as a peer, and to translate model behavior into member experience.
A track record of driving cross-team programs with many dependencies and no direct authority.
Sound business judgment: you can quantify a tradeoff, reason about cost, and decline work that will not pay for itself.
Comfort operating in ambiguity, with evidence of turning a broad set of possibilities into one well-scoped bet.
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.

Nice To Haves

internal AI tooling or evaluation frameworks
experience partnering with a research organization
wearables or sensor data
SQL or light scripting

Responsibilities

Shape how AI output quality is measured across WHOOP's AI experiences, including the evaluation methodology, datasets, and scoring that make quality continuous and trusted rather than judged case by case.
Build the evaluation habit across the company: make evals self-serve, and get the teams shipping AI features to actually run them.
Help decide which models power which experiences, and which providers we run them on, balancing quality, latency, and cost as the model landscape shifts.
Product-manage our internal AI development platform and drive its adoption, so that anyone at WHOOP building with AI has a fast, well-instrumented path from idea to shipped.
Track the unit economics of AI at WHOOP, including cost per interaction, and drive the tradeoffs between quality, latency, and spend.
Explore where AI capability goes next, from fine-tuning and reinforcement learning to distillation and emerging foundation models, and turn a broad field of options into a small number of well-scoped bets, starting with internal productivity.