At WHOOP, we're on a mission to unlock and inspire performance for life. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives.
WHOOP is seeking a Senior Edge Signal Processing Engineer to join the Sensor Intelligence Group (SIG), a cross-functional team collaborating across WHOOP Labs, Firmware, and Machine Learning and Research. This role is central to developing next-generation sensor processing to enable foundational health features at WHOOP. You’ll develop the edge signal processing underpinning WHOOP physiological insights and coaching, ultimately delivering meaningful and personalized feedback to millions of members.
Responsibilities
Lead the design and development of real-time signal processing and edge inference for consumer products
Own the full development lifecycle, from prototyping and validation through productization and continuous improvement
Evaluate commercial solutions, develop prototypes and 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
Qualifications
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 (physiological, audio, motion, or related modalities)
Strong foundation in signal processing fundamentals (e.g., filtering, spectral analysis, time-frequency methods)
Demonstrated experience integrating signal-processing components into end-to-end embedded systems
Ability to implement and optimize signal-processing algorithms for constrained compute, memory, latency, and power budgets
Experience integrating third-party libraries, frameworks, or algorithm IP
Proficiency in Python or MATLAB for algorithm prototyping and with C/C++ for deployment to embedded product platforms
Excellent communication skills, including the ability to present technical results to a diverse audience
Demonstrated creativity, adaptability, and a strong interest in translating prototypes into products
Additional Desired Experience
Experience deploying signal processing algorithms to battery-powered consumer product platforms
Familiarity with adaptive signal processing, multi-sensor processing, signal enhancement, detection, or classification techniques
Experience developing and evaluating hybrid DSP/ML systems
Familiarity with embedded firmware, RTOS environments, and real-time processing pipelines
Experience using optimized MCU/DSP libraries and acceleration frameworks (e.g., CMSIS-DSP, CMSIS-NN, or vendor-specific libraries)
Experience with fixed-point implementation, quantization, or other numerical optimization techniques for embedded signal processing
Skills Required
- Bachelor's degree in Electrical Engineering or a related field
- 5+ years developing and deploying real-time sensor signal processing algorithms
- Strong foundation in filtering, spectral analysis, and time-frequency signal processing methods
- Experience integrating signal-processing components into end-to-end embedded systems
- Ability to optimize algorithms for constrained compute, memory, latency, and power budgets
- Experience integrating third-party libraries, frameworks, or algorithm intellectual property
- Proficiency with Python or MATLAB for prototyping
- Proficiency with C or C++ for embedded deployment
- Excellent communication skills and ability to present technical results
- Creativity, adaptability, and interest in translating prototypes into products
- Master's degree or PhD
- Experience deploying algorithms to battery-powered consumer products
- Familiarity with adaptive signal processing, multisensor processing, signal enhancement, detection, or classification
- Experience developing and evaluating hybrid DSP and machine learning systems
- Familiarity with embedded firmware, RTOS environments, and real-time processing pipelines
- Experience with optimized MCU/DSP libraries and acceleration frameworks such as CMSIS-DSP or CMSIS-NN
- Experience with fixed-point implementation, quantization, or numerical optimization for embedded signal processing
What the Team is Saying
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WHOOP Compensation & Benefits Highlights
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Healthcare Strength — Health coverage is considered a strong part of the package, including medical, dental, and vision insurance. Feedback suggests the plans are solid and align with a health-focused culture.
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Parental & Family Support — Paid parental leave is notably generous, with additional transition time for returning to work. This breadth stands out as a meaningful family support.
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Wellbeing & Lifestyle Benefits — Wellness perks are extensive, including a wellness stipend, free membership/device with an extra to gift, daily meals at HQ, gym/recovery access, and a sleep-performance bonus. Feedback suggests these health-aligned perks add tangible value to total rewards.
WHOOP Insights
What We Do
At WHOOP, we’re on a mission to unlock human performance. WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Our wearable device and performance optimization platform has been adopted by many of the world's greatest athletes and consumers alike.
Why Work With Us
At WHOOP, we’re focused on building an inclusive and equitable team with a strong sense of belonging for everyone—increasing representation in every way as our team grows. We believe that our differences are our source of strength—so much so it’s one of our core values.
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WHOOP Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
