3 hours ago
Responsibilities
- Own the end-to-end porting of validated Sensor Intelligence algorithms from reference environments to production-ready WHOOP embedded platforms.
- Translate Python, MATLAB, and similar reference implementations into optimized C/C++ for real-time, resource-constrained execution.
- Resolve dependencies across cloud, mobile, connectivity, sensor pipelines, libraries, and platform services for on-device execution.
- Integrate algorithms with firmware, sensor pipelines, embedded services, and Edge ML platform capabilities.
- Establish functional and numerical equivalence, profile on-device performance, and debug cross-system issues.
- Develop reusable tools, test harnesses, profiling infrastructure, and deployment patterns for algorithm migration across hardware platforms.
Requirements
- BS or MS in Computer Engineering, Electrical Engineering, Computer Science, or a related technical field, or equivalent practical experience.
- Strong C/C++ development experience with embedded, real-time, or resource-constrained systems.
- Experience porting, integrating, or optimizing signal-processing or machine-learning algorithms for MCU-based, embedded, or edge platforms.
- Experience translating algorithms from Python, MATLAB, or similar reference environments.
- Experience profiling and optimizing embedded software for runtime, memory footprint, computational efficiency, or power, with strong debugging skills.
- Strong systems thinking, software integration, and cross-functional collaboration skills.
- Experience with embedded optimization technologies or techniques such as DSP optimization, fixed-point implementation, quantization, model compression, ARM Cortex-M, DSPs, NPUs, RTOS environments, CMSIS-DSP, CMSIS-NN, or TensorFlow Lite Micro.
- Experience with physiological sensing, wearable devices, time-series sensor data, low-power systems, or reference-to-embedded equivalence is a plus.
- Commitment to using AI tools responsibly while maintaining high-quality work.
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.