Staff Applied Machine Learning Scientist

The role

You will develop and improve production-ready edge algorithms that transform sensor data into physiological insights. You will work with a cross-functional team to solve problems at the intersection of wearable sensing, physiological modeling, and applied AI.

What you will do

• Design advanced algorithms combining signal processing, physiological modeling, machine learning, and deep learning.
• Own development and continuous improvement of production-ready edge algorithms.
• Analyze large-scale wearable sensor datasets to drive algorithm improvements.
• Define evaluation methodologies, validation frameworks, and performance metrics.
• Optimize algorithms for embedded deployment regarding power, memory, latency, and compute.
• Set technical direction and establish best practices for modeling and validation.
• Pursue high-impact technical initiatives from research through production deployment.
• Collaborate with Data Science, Firmware, Software, Hardware, Product, and domain experts.
• Stay at the forefront of advances in deep learning, machine learning, signal processing, edge AI, and physiological sensing.

Required qualifications

• MS or PhD in Electrical Engineering, Biomedical Engineering, Computer Science, Machine Learning, Applied Mathematics, or a related quantitative field.
• 7+ years of experience developing and deploying machine learning, deep learning, and/or signal processing algorithms for complex real-world applications.
• Deep technical expertise in modern machine learning and deep learning methods for time-series and multimodal sensor data.
• Strong foundation in digital and statistical signal processing.
• Strong proficiency in Python for algorithm development, experimentation, and large-scale data analysis.
• Ability to develop robust models using large, noisy, real-world datasets.
• Experience designing rigorous experiments, defining performance metrics, and performing error analysis.
• Experience taking algorithms through the full development lifecycle.
• Strong analytical and problem-solving skills.

Nice to have

• Experience with C/C++ and embedded algorithm development
• Experience with physiological signals, wearable sensors, or biomedical sensing
• Experience optimizing algorithms for resource-constrained embedded or edge environments

About the company

WHOOP empowers members to perform at a higher level through a deeper understanding of their bodies and daily lives. Their wearable technology collects physiological data to provide insights into recovery, training, and sleep.