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Senior Sensor Intelligence Engineer (Embedded)

Whoop
Boston, USA
Full-time
Senior
Onsite
Discovered 1 months ago
matlabpython

Full Job Posting

RESPONSIBILITIES:

  • Develop signal-processing and machine-learning algorithms that interpret physiological, motion, and other wearable sensor signals, including applications such as activity and state detection, wear detection, signal-quality assessment, and device-state estimation
  • Design intelligent embedded control strategies that dynamically configure sensor behavior based on signal quality, device state, user context, system requirements, and power constraints
  • Characterize new and existing sensors by understanding signal behavior, noise sources, artifacts, dynamic range, sampling requirements, calibration, operating modes, and the impact of analog and acquisition architectures
  • Prototype algorithms and sensing strategies using tools such as Python or MATLAB, then partner with Firmware Engineering to translate them into robust, computationally efficient implementations suitable for resource-constrained embedded systems
  • Partner closely with Firmware, Electrical Engineering, Data Science, Hardware, and broader Sensor Intelligence teams to bring up new sensing modalities, debug issues across the sensing stack, and inform sensing architectures for future WHOOP products
  • Develop experiments, analysis frameworks, and validation methodologies to evaluate sensor and algorithm performance across users and real-world conditions, optimizing solutions for accuracy, robustness, latency, memory, compute, and power

QUALIFICATIONS:

  • 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, with experience applying techniques such as filtering, spectral analysis, sampling theory, noise reduction, and feature extraction to real-world sensor data
  • Experience developing signal-processing and/or machine-learning algorithms for noisy, artifact-prone sensor data and taking algorithms beyond 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++ and embedded-system considerations such as timing, memory, compute, and hardware interfaces
  • Working knowledge of sensor and electrical systems, including concepts such as ADCs, analog front ends, sampling, digital interfaces, noise, calibration, and signal acquisition
  • Ability to investigate and solve ambiguous engineering problems across algorithm, firmware, sensor, and electrical boundaries using strong 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
  • Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work aligns with the same high-quality standards as personal contributions.
  • Interested in the role, but don't meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
  • WHOOP is an Equal Opportunity Employer and participates in E-Verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Preferred Qualifications

  • 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

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