Sensor Intelligence Engineer II (Advanced Development)

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 looking for an Engineer II to join the Sensor Intelligence Group (SIG), a cross-functional team collaborating across Hardware, Firmware, and Data Science. This role will focus on advancing WHOOP’s mission of integrating cutting edge sensors that deliver physiological insight into our products.

Success in this role will require a deep understanding of physical sensing mechanisms, for example electrical, optical, or thermal, and development of the signal processing and algorithms needed to translate raw data into actionable feedback.

RESPONSIBILITIES:

• Become the subject matter expert of a sensor modality, responsible for constructing and managing performance requirements and design sensitivities
• Process raw data and implement signal processing and algorithmic approaches to evaluate sensor performance and advance new product features
• Design hardware and human studies to capture data sets that are required for sensor and feature development
• Collaborate with Hardware and Firmware engineers to give feedback on prototype and product design
• Clearly communicate technical learnings to a multifunctional audience so that the team can efficiently navigate through a complex decision space

QUALIFICATIONS:

• Bachelor's degree in Electrical/Computer Engineering, Biomedical Engineering, or a related field; Master’s or PhD degree preferred
• 3+ years of experience as a hands-on engineer or scientist with a focus on leading early stage sensor design from concept to completion
• Experience with Python and or Matlab for data analysis, signal processing, machine learning
• Familiarity with electrical and optical laboratory characterization equipment
• Excellent written and verbal communication skills.
• Innovative, knowledgeable, and able to adapt to changing requirements while still producing quality algorithms with tight deadlines