12 hours ago
Base Salary
$150k - $215k/yr
Responsibilities
- Design algorithms combining signal processing, feature extraction, and machine learning for physiological insights from wearable sensor data.
- Analyze noisy sensor datasets, train and evaluate models, identify performance gaps, and improve accuracy, robustness, and generalization.
- Translate prototypes and trained models into production-ready C/C++ implementations optimized for accuracy, power, memory, compute, and latency.
- Integrate algorithms into production firmware, validate them on target hardware, and resolve differences between prototype and embedded performance.
- Define metrics and validation plans spanning offline evaluation, lab experiments, real-world analysis, and on-device testing.
- Collaborate with Data Science, Firmware, Hardware, Software, Product, and domain experts to deliver and continuously improve production capabilities.
Requirements
- At least 5 years of experience developing signal-processing and machine-learning algorithms for time-series or sensor data in real-world applications.
- MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, or a related quantitative field, or equivalent practical experience.
- Strong foundation in digital and statistical signal processing for noisy time-series data; physiological-signal or wearable-sensor experience is a plus.
- Proficiency in Python for data analysis, model development, and experimentation, plus C/C++ for efficient embedded-firmware algorithms.
- Experience developing, training, and evaluating models with TensorFlow, PyTorch, or scikit-learn.
- Experience deploying machine-learning models to resource-constrained embedded systems and optimizing accuracy, power, memory, compute, and latency.
- Ability to independently investigate complex algorithmic problems, design rigorous validation experiments, and communicate technical tradeoffs across engineering and data-science teams.
- Commitment to using AI tools while maintaining the same quality standards as personal contributions.
Benefits
- The role is based in WHOOP's Boston, Massachusetts office and may require relocation.
Categories
About WHOOP
WHOOP builds a wearable health and performance tracker paired with an analytics app that measures sleep, recovery, and strain for athletes and health‑conscious consumers. Its business model combines device sales with a recurring membership that unlocks coaching features and insights. Founded in 2012 and headquartered in Boston, the privately held company also serves enterprise wellness programs and sports organizations seeking continuous performance monitoring.