Senior Signal Processing Engineer (Applied Algorithms)

About the Role

WHOOP is seeking a Senior Signal Processing Engineer to develop and deploy algorithms for physiological sensors—including optical sensor and inertial measurement unit (IMU) data—into accurate, reliable, and real-time insights on WHOOP devices. This hands-on role centers on digital and statistical signal processing, sensor fusion, and model-based state estimation, with a particular focus on accelerometer and gyroscope data.

You will own algorithm development from sensor characterization, mathematical modeling, and Python prototyping through efficient C/C++ implementation, firmware integration, and production validation. Working closely with Firmware, Hardware, Data Science, and Product, you will deliver robust on-device algorithms that meet the constraints of wearable hardware.

Responsibilities

• Design and develop real-time signal processing and sensor fusion algorithms that combine sensor measurements to characterize motion and deliver reliable insights.
• Develop and tune model-based estimators for orientation and motion, including sensor bias estimation, uncertainty propagation, and drift mitigation.
• Build robust IMU processing pipelines, including filtering, calibration, time synchronization, resampling, coordinate transformations, and sensor noise compensation.
• Analyze large-scale, noisy wearable datasets to identify failure modes and improve robustness across motion patterns, device orientation, fit, and movement characteristics.
• Translate algorithm prototypes into production-ready C/C++ implementations, balancing accuracy with power, memory, compute, numerical stability, and latency.
• Partner with Firmware and Hardware teams on sensor configuration, sampling strategies, and on-device integration; investigate differences between prototype behavior and target hardware performance.
• Define performance metrics and validation plans using reference measurements, controlled experiments, real-world data, and on-device testing.
• Own technical decisions for algorithm components, contribute to design and code reviews, mentor teammates, and collaborate across functions to investigate post-deployment issues.

Qualifications

• 5+ years of experience developing and deploying signal processing, sensor fusion, or state-estimation algorithms for real-world sensor applications, including hands-on work with IMU data.
• MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Applied Mathematics, or a related quantitative field, or equivalent practical experience.
• Strong foundation in digital and statistical signal processing, including filtering, spectral analysis, stochastic processes, and sensor noise characterization.
• Demonstrated experience with accelerometer and gyroscope processing, IMU calibration, sensor error modeling, bias estimation, and drift management.
• Strong experience with Kalman filtering (including extended or error-state formulations) and model-based sensor fusion, with understanding of nonlinear estimation and uncertainty propagation.
• Practical knowledge of 3D motion and orientation representations (coordinate frames, rotation matrices, quaternions, rigid-body kinematics).
• Proficiency in Python for algorithm development, data analysis, and experimentation, and C/C++ for efficient embedded implementation on resource-constrained hardware.
• Ability to independently investigate complex algorithmic problems, design validation experiments, and communicate technical tradeoffs.
• Experience with body-worn sensors, human-motion modeling, motion segmentation, or periodicity analysis is highly desirable.

Location & Relocation

This role is based in the WHOOP office in Boston, MA. Candidates must be prepared to relocate if necessary to work on-site.