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ashby

Staff Applied Machine Learning Scientist

Whoop
Boston, USA
Full-time
Senior · 7+ years experience
Onsite
Discovered 2 weeks ago
python

Full Job Posting

RESPONSIBILITIES:

  • Design advanced algorithms that combine signal processing, physiological modeling, machine learning, and deep learning for physiological time-series and multimodal sensor data, with a focus on accuracy, robustness, and generalization across diverse members and real-world conditions.
  • Own the development and continuous improvement of production-ready edge algorithms that transform multimodal sensor data into accurate, reliable, and real-time physiological insights.
  • Analyze large-scale wearable sensor datasets to identify performance gaps, characterize challenging conditions, and drive data-informed algorithm improvements.
  • Define rigorous evaluation methodologies, validation frameworks, and performance metrics to assess algorithms throughout development and deployment.
  • Optimize algorithms for embedded deployment, balancing accuracy with power, memory, latency, and compute constraints across current and future wearable platforms.
  • Set technical direction and establish best practices for modeling, experimentation, validation, and algorithm development across complex sensing problems.
  • Pursue ambiguous, high-impact technical initiatives from research and prototyping through validation, production deployment, monitoring, and continuous improvement.
  • Collaborate closely with Data Science, Firmware, Software, Hardware, Product, and domain experts to translate algorithmic innovations into production-ready capabilities and member-facing features.
  • Stay at the forefront of advances in deep learning, machine learning, signal processing, edge AI, and physiological sensing, and translate relevant innovations into differentiated WHOOP capabilities.

QUALIFICATIONS:

  • MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
  • 7+ years of experience developing and deploying machine learning, deep learning, and/or signal processing algorithms for complex real-world applications.
  • Deep technical expertise in modern machine learning and deep learning methods, particularly for time-series and multimodal sensor data.
  • Strong foundation in digital and statistical signal processing, with the ability to combine classical signal processing techniques with modern learning-based approaches.
  • Strong proficiency in Python for algorithm development, experimentation, and large-scale data analysis; experience with C/C++ and embedded algorithm development is highly desirable.
  • Demonstrated ability to develop robust models using large, noisy, real-world datasets and achieve strong generalization across diverse conditions.
  • Experience designing rigorous experiments, defining performance metrics, performing error analysis, and translating findings into algorithm improvements.
  • Experience taking algorithms through the full development lifecycle, from research and prototyping through validation, deployment, monitoring, and continuous improvement.
  • Strong analytical and problem-solving skills, with the ability to navigate ambiguity and make sound technical decisions.
  • Experience with physiological signals, wearable sensors, or biomedical sensing is highly desirable.
  • Experience optimizing algorithms for resource-constrained embedded or edge environments, including tradeoffs across accuracy, power, memory, compute, and latency, is a plus.
  • Strong commitment to embracing and leveraging AI tools in day-to-day work while maintaining high standards for quality and rigor.
  • Join us in pushing the boundaries of wearable sensing, applied AI, and physiological intelligence and positively impacting people’s lives!
  • 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.

Preferred Qualifications

  • Experience optimizing algorithms for resource-constrained embedded or edge environments, including tradeoffs across accuracy, power, memory, compute, and latency, is a plus.

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