Senior Sensor Intelligence Engineer (Tools & Validation)

WHOOP is seeking a Senior Sensor Intelligence Engineer to help develop, validate, and scale the sensor algorithms and tools that transform noisy physiological signals into meaningful member insights. As part of a cross-functional team spanning Sensor Intelligence, Hardware, ML Research, WHOOP Labs, Firmware, Apparel & Accessories, and other engineering disciplines, you will develop robust algorithm verification and validation methodologies, evaluate sensor and algorithm performance against appropriate reference data, build diagnostic and analysis tools, characterize failure modes, and help determine algorithm readiness for real-world deployment across our diverse member population.

RESPONSIBILITIES:

• Develop end-to-end verification and validation methodologies for sensor algorithms and biosensor systems, including test design, reference-data comparison, performance metrics, acceptance criteria, and readiness assessment across large-scale datasets
• Partner with Data Science, WHOOP Labs, Research, Firmware, and other engineering teams to design representative data collections, evaluate algorithm performance against reference measurements, characterize failure modes, and determine readiness for real-world deployment
• Apply signal processing, statistical analysis, and machine learning techniques to physiological time-series data to identify performance opportunities, investigate algorithm failures, and improve sensor-derived insights
• Build and maintain scalable workflows, dashboards, and diagnostic tools for algorithm validation, regression testing, performance monitoring, data quality assessment, and sensor behavior across diverse populations and use cases
• Contribute to software development, debugging, testing, and validation processes, ensuring analytical tools, algorithms, and results meet production-quality standards
• Communicate findings through clear technical documentation, reports, and visualizations that enable cross-functional teams to make informed product and engineering decisions

QUALIFICATIONS:

• Bachelor’s or Master’s degree in electrical engineering, biomedical engineering, applied mathematics, statistics, computer science, or a related quantitative field, or equivalent practical experience
• 5+ years of industry or research experience working with signal processing, machine learning, statistical analysis, algorithm validation, or related quantitative methods
• Experience analyzing time-series data and applying core signal processing techniques such as filtering, spectral analysis, peak detection, and windowing
• Demonstrated experience independently designing and driving validations studies, including one or more of test methodology development, reference-data comparison, performance evaluation, acceptance-criteria definition, or failure-mode investigation.
• Proven track record of investigating intricate or ill-defined technical challenges, pinpointing root causes, and delivering solutions across algorithm, sensor, data, and system domains
• Proficiency in Python and/or C, with experience developing reliable tools or software for data processing, analysis, or algorithm validation
• Strong foundation in statistical inference and experimental analysis, including the ability to select appropriate methods, interpret results, and communicate analytical trade-offs
• Experience working with large datasets and modern engineering or data infrastructure such as Git, CI/CD systems, cloud platforms, or data warehouses
• Strong written and verbal communication skills, with the ability to translate complex technical findings into concise documentation, visualizations, and actionable recommendations
• 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.