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Whoop

Associate Director, Machine Learning (Core Algorithms)

Boston, MAOnsite · United States
Director+ · FullTime · Machine Learning & AI Research
POSTED 13 JULVERIFIED 7M AGO
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Pay · Whoop
$191k–$200k
p25–p75 · n=3
Open for
113d
since 13 Jul
H-1B · FY26
24
certified LCAs
Hiring · 30d
125
−4 net · open roles

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer through a deeper understanding of their bodies and daily lives.

We are seeking an Associate Director, Core Algorithms (Cloud) to lead the teams responsible for WHOOP's cloud-based algorithmic intelligence — the models and systems that transform physiological data into the sleep, recovery, and training insights our members rely on daily. This role is also responsible for ensuring our cloud algorithms evolve alongside WHOOP hardware, partnering with Sensor Intelligence and Hardware teams to translate new sensor capabilities into production-grade algorithmic experiences.

You will own the technical vision, execution, and organizational health of this team. You'll drive the evolution of our core production algorithms such as workout detection, strain, and sleep staging toward higher accuracy, better member experiences, and more mature development practices. You will partner closely with ML Platform, Sensor Intelligence, Research, Product, and Software Engineering to define what WHOOP algorithms can enable — not just how they perform technically, but how they show up for members.

This is a role for someone who has built and shipped physiological ML at scale in a consumer product, who has a deep product instinct for what algorithms mean to end users, and who knows how to elevate an ML organization's practices: raising the bar on tooling, processes, and standards to match the ambition of the work.

RESPONSIBILITIES

Lead the cloud ML team responsible for the algorithms powering sleep, recovery, and training

Directly manage applied ML scientists and ML engineers; provide coaching, career development, and performance feedback that grows individual contributors into strong technical leaders

Ensure the technical quality bar for algorithm development is maintained by establishing the processes, reviews, and standards that guarantee rigor from research through deployment, and diving into designs and architectural decisions where necessary

Help drive the vision for what WHOOP algorithms and next-generation sensors can enable; advocate for member experience and push the boundaries of what our data makes possible

Ensure cloud algorithms remain compatible with future hardware generations; partner with Sensor Intelligence and Hardware to evolve proof-of-concept algorithms that leverage new sensor capabilities and bring them to production readiness

Establish and improve development lifecycle practices: experiment management, model validation, deployment pipelines, and production monitoring

Partner with ML Platform / MLOps to define requirements and drive maturity improvements across experiment tracking, model monitoring, deployment automation, and observability

Drive cross-functional alignment with Sensor Intelligence, Product, Software Engineering, and Research teams

QUALIFICATIONS

8+ years of experience in machine learning or applied data science, with hands-on experience developing and shipping ML models for a consumer product

4+ years of people leadership experience directly managing machine learning scientists/engineers, with demonstrated growth of team members and a track record of building high-performing teams

Experience scaling a production ML organization: growing teams and leaders, identifying gaps in the development lifecycle, and driving improvements that increase velocity, reliability, and rigor

Deep product sense: ability to think about algorithms from the member's perspective, drive the vision for what algorithms can enable, and ensure the team is building toward meaningful user outcomes

Ability to evaluate technical designs, guide architectural decisions, and ensure quality at the system level, without needing to write code day-to-day

Experience defining and driving cross-functional programs with engineering, product, and science partners

Strong communication skills with the ability to translate complex ML concepts to diverse audiences including product, engineering, and executive stakeholders

Source · WhoopFirst seen 2 NovOriginal ↗