4 hours ago
Responsibilities
- Develop signal-processing and machine-learning algorithms for physiological, motion, and wearable sensor signals.
- Design embedded control strategies that dynamically configure sensor behavior based on signal quality, device state, user context, system requirements, and power constraints.
- Characterize sensors across signal behavior, noise, artifacts, dynamic range, sampling, calibration, operating modes, and analog/acquisition architectures.
- Prototype algorithms and sensing strategies using Python, MATLAB, or similar environments and translate them into efficient embedded implementations with Firmware Engineering.
- Collaborate with Firmware, Electrical Engineering, Data Science, Hardware, and Sensor Intelligence teams to bring up sensing modalities and debug cross-stack issues.
- Develop experiments, analysis frameworks, and validation methods to optimize accuracy, robustness, latency, memory, compute, and power.
Requirements
- BS, MS, or PhD in Electrical Engineering, Computer Engineering, Biomedical Engineering, Computer Science, Applied Physics, or a related technical field, or equivalent practical experience.
- Strong foundation in digital signal processing and time-series analysis, including filtering, spectral analysis, sampling theory, noise reduction, and feature extraction.
- Experience developing algorithms for noisy sensor data and progressing them from offline analysis toward real-time, embedded, or production implementation.
- Strong proficiency in Python, MATLAB, or similar algorithm-development environments, with working knowledge of C/C++.
- Working knowledge of sensor and electrical systems, including ADCs, analog front ends, sampling, digital interfaces, noise, calibration, and signal acquisition.
- Ability to solve ambiguous engineering problems across algorithm, firmware, sensor, and electrical boundaries using experimental and analytical methods.
- Experience with wearable, physiological, optical, impedance, motion, multimodal, or related sensor systems is valued.
- Experience with embedded inference, sensor fusion, fixed-point processing, quantization, low-power sensing, or microcontroller deployment is a plus.
- Commitment to using AI tools while maintaining the same quality standards as personal contributions.
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.