Sensor Intelligence Engineer II (Embedded Machine Learning)
Job Description
WHOOP is a pioneering company in the health and performance technology sector, focused on unlocking human performance and healthspan through wearable technology. As a Sensor Intelligence Engineer II, you'll join a dynamic cross-functional team working on fundamental features that directly impact user experience and health monitoring capabilities.
The role combines expertise in machine learning, embedded systems, and signal processing to tackle the complex challenge of extracting meaningful physiological information from noisy sensor data. You'll be working with cutting-edge technology, designing and implementing algorithms that must perform efficiently on resource-constrained edge devices while maintaining high accuracy and reliability.
This position offers a unique opportunity to work at the intersection of hardware and software, developing solutions that directly impact people's health and wellness. You'll collaborate with diverse teams including Data Scientists, Firmware Engineers, and Research teams, contributing to the full development lifecycle from conception to deployment.
The ideal candidate will bring a strong foundation in signal processing and machine learning, with practical experience in embedded systems development. You'll need to balance technical expertise with creative problem-solving skills, as you'll be working on optimizing algorithms for both performance and power efficiency.
Located in Boston, MA, this role offers the chance to work with a company that's pushing the boundaries of wearable technology. WHOOP values diversity and encourages applications from candidates who might not meet every qualification but demonstrate strong potential and character. The company maintains an inclusive environment and participates in E-verify for employment eligibility.
Responsibilities For Sensor Intelligence Engineer II (Embedded Machine Learning)
- Design, optimize and maintain machine learning algorithm on the edge device
- Collaborate with Data Science, Firmware, and Research teams to enhance user metrics
- Design, prototype, and implement machine learning solutions for low-power embedded systems
- Participate in full software development lifecycle including development, debugging, and testing
- Leverage expertise in signal processing and embedded ML to optimize biosensor systems
- Explore and implement algorithms balancing performance and power efficiency
- Contribute to research efforts for hardware-aware model optimization
Requirements For Sensor Intelligence Engineer II (Embedded Machine Learning)
- Bachelor's or Master's degree in applied mathematics, electrical/biomedical engineering, computer engineering, or related field
- 2+ years of industry or research experience in signal processing and/or machine learning
- Understanding of biosensor systems and analysis of physiological signals
- Strong programming proficiency in C and/or Python
- Experience developing and optimizing machine learning models for edge devices
- Working knowledge of adaptive signal processing and time-series analysis
- Deep understanding of ML libraries such as TensorFlow Lite, scikit-learn, PyTorch, or TinyML frameworks
- Excellent communication skills
- Demonstrated creativity, adaptability, and passion for building impactful products
