Associate Director, Machine Learning (Core Algorithms) at Whoop
Boston, MA
$200,000–$245,000from the description
Jun 29, 2026
Boston, MA
Jul 21, 2026
What this job asks for AI summary
A leadership role overseeing the cloud-based machine learning team that builds and maintains the algorithms behind sleep staging, recovery, and workout detection in a consumer wearable product. The position involves managing applied ML scientists and engineers, setting technical standards across the full model development lifecycle, and coordinating with hardware, sensor, product, and platform teams to bring new sensor capabilities into production algorithms. Best suited to someone with a background in shipping physiological or wearable ML at scale who has also led ML teams.
Senior level · 8+ years · Boston, MA · Full-time
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
What the occupation pays Median $214,960 (middle half $174,270–$269,520). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (7)
This is a people-management role (Associate Director) with direct reports, coaching, and org-building responsibilities — 11-3021 is the primary classification. However, the role also demands deep hands-on ML expertise and technical architectural judgment, making 15-2051 a meaningful runner-up.
The title 'Associate Director' carries no standard seniority-band word (Junior/Mid/Senior/Staff/Principal), so the title states no level. The actual scope — managing a team, 8+ years required, org-level impact — supports Senior.
The 8+ years figure is the overall ML/data science experience requirement; the 4+ years figure is specifically for people leadership. Both are role-level gates, not tied to a named technology.
'ML model development' and 'ML model deployment' are listed as required capabilities in the Qualifications section framed around shipping ML models for a consumer product at scale.
Physiological/wearable sensor experience (PPG, accelerometer, temperature, bioimpedance) and time-series modeling appear under the 'PREFERRED' heading — listed as preferred, not required.
No specific ML framework, cloud platform, or programming language is named anywhere in the posting; the skills extracted reflect the functional capabilities explicitly called out.
Ignored 3 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): ML model development, people management, time-series modeling.
Read the full posting
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