Health Sensing Engineer

Google Google · Big Tech · Mountain View, CA +1

This role focuses on developing custom silicon solutions for Google's direct-to-consumer health products, involving the interpretation of health-related data from wearable sensors using machine learning/deep learning models. The engineer will also design, build, and validate new wearable sensors and collaborate on user studies, particularly for Software as a Medical Device (SaMD).

What you'd actually do

  1. Use simulation tools to develop models of tissue-light interaction, thermal behavior, and other bodily responses.
  2. Develop and implement machine learning/deep learning models for interpreting health-related data from wearable sensors.
  3. Design user studies and collaborate with clinical professionals to validate sensor accuracy, particularly for Software as a Medical Device.
  4. Extract significant insights from high-throughput time-series health data.
  5. Design, build, and validate new wearable sensors (e.g., optical, electrical, thermal); implement benchtop set up in Lab and also on-body testing for sensor evaluation across user populations.

Skills

Required

  • Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
  • 4 years of experience working in a consumer devices health sensing technical environment.
  • Experience with one or more of the following sensors: optical sensors, lasers, MEMS, temperature, RF, or chemical sensors.

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
  • Experience in machine learning frameworks, statistical analysis, and signal processing for high-throughput health data.
  • Experience with clinical and laboratory research methodologies, including study design and SaMD regulatory requirements.
  • Track record in developing sophisticated health systems with a focus on human physiology and advanced modeling.

What the JD emphasized

  • Software as a Medical Device
  • SaMD regulatory requirements

Other signals

  • developing custom silicon solutions
  • interpreting health-related data from wearable sensors
  • Software as a Medical Device
  • high-throughput time-series health data
  • design, build, and validate new wearable sensors