Associate Director, Machine Learning (Core Algorithms)

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Boston, MA, USA
Hybrid
Senior level
Fitness • Hardware • Healthtech • Sports • Wearables
Power your performance with 24/7 data
The Role
Lead WHOOP's cloud-based core algorithm teams to develop, validate, and productionize models for sleep, recovery, and training. Drive technical vision, cross-functional alignment with Sensor Intelligence and Hardware, improve ML lifecycle practices (experiment tracking, deployment, monitoring), and manage and grow applied ML scientists and engineers to deliver better member experiences.
Summary Generated by Built In

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

PREFERRED

    • Experience building algorithms using physiological or wearable sensor data (e.g., PPG, accelerometer, temperature, bioimpedance)

    • Experience managing through hardware-coupled development timelines where sensor availability and device generations constrain algorithm roadmaps

    • Familiarity with time-series modeling, sequential data, and the specific challenges of continuous physiological monitoring

Skills Required

  • 8+ years 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
  • Experience scaling a production ML organization and improving development lifecycle (velocity, reliability, rigor)
  • Deep product sense for translating algorithms into meaningful user outcomes
  • Ability to evaluate technical designs and guide architectural decisions without writing code day-to-day
  • Experience defining and driving cross-functional programs with engineering, product, and science partners
  • Strong communication skills translating complex ML concepts to product, engineering, and executives
  • Experience building algorithms using physiological or wearable sensor data (PPG, accelerometer, temperature, bioimpedance)
  • Experience managing hardware-coupled development timelines where sensor availability constrains roadmaps
  • Familiarity with time-series modeling, sequential data, and continuous physiological monitoring challenges

What the Team is Saying

Josh
Manan Dedhia
Anahis

WHOOP Compensation & Benefits Highlights

  • Parental & Family Support Parental leave is described as generous, with an additional transition period to support return-to-work. Feedback suggests this policy stands out within the overall package.
  • Wellbeing & Lifestyle Benefits Wellness stipends, free WHOOP memberships (including a giftable one), a sleep-performance cash incentive, daily meals, and access to onsite gym and recovery tools create a lifestyle-oriented offering. Feedback suggests these perks meaningfully enhance the total rewards experience beyond base pay.
  • Equity Value & Accessibility Equity participation and stock option eligibility are highlighted, and ownership is portrayed as rewarding as the company grows. Feedback suggests this sense of ownership positively influences perceptions of compensation.

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The Company
HQ: Boston, MA
500 Employees
Year Founded: 2012

What We Do

At WHOOP, we’re on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable device and performance optimization platform has been adopted by many of the world's greatest athletes and consumers alike.

Why Work With Us

At WHOOP, we’re focused on building an inclusive and equitable team with a strong sense of belonging for everyone—increasing representation in every way as our team grows. We believe that our differences are our source of strength—so much so it’s one of our core values.


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WHOOP Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Typical time on-site: 4 days a week
HQBoston, MA
Limerick, Limerick, V94 4D83 Ireland
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