Lead design and deployment of real-time sensor signal processing algorithms for edge inference on consumer wearables. Requires 5+ years experience with embedded DSP platforms, Python/MATLAB prototyping, and C/C++ deployment.
Salary not listed
On-site5+ YOEEmbedded Engineering
About the role
Responsibilities
Lead the design and development of signal processing for real-time, edge inference on consumer products
Own the full lifecycle: prototyping, validation, productionization, and continuous improvement
Evaluate commercial solutions; create demos and inform build/buy decisions
Collaborate cross-functionally with hardware, software, and product teams to bring algorithms to WHOOP members
Mentor junior engineers and contribute to a high-performance, research-to-production culture
Requirements
B.S. in Electrical Engineering or related field (M.S. or PhD preferred)
5+ years of experience developing and deploying real-time sensor signal processing algorithms (e.g., physiological, audio, motion)
Demonstrated experience deploying algorithms to consumer product embedded platforms (e.g., fixed-point DSPs or MCUs)
Strong foundation in signal processing fundamentals (filtering, spectral analysis, time-frequency methods)
Experience with system-level design and optimization to maximize product battery life
Proficiency in Python or MATLAB for algorithm prototyping and with C/C++ for deployment to embedded product platforms
Excellent communication skills
Nice-to-Haves
Experience developing hybrid DSP/ML systems, with a focus on signal pre-processing and/or feature extraction
Knowledge of embedded systems, RTOS, or firmware development
Deep understanding of sensor physics or sensor fusion techniques
Knowledge of microcontroller libraries for efficient signal processing (e.g., CMSIS-DSP or CMSIS-NN)
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