Senior ML Engineer, Biosignal & Health Modeling

About Oura

Our mission at Oura is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We’ve helped 2.5 million people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles. Empowering the world starts with living our values and empowering our team.

Job Summary

We’re now hiring a Senior Algorithm Engineer (Biosignal Processing) to join our Future Physiology team. This role is ideal for a technically curious and hands-on engineer or scientist with deep expertise in biosignal processing, particularly PPG, spectroscopy, or related physiological sensing modalities.

Key Responsibilities

• Develop advanced signal processing and physiological inference algorithms to extract physiological metrics from multimodal, time-series biosignals (PPG, motion, temperature, spectroscopy, etc.).
• Design, prototype, and refine methods that transform noisy, artifact-prone time-series data into reliable health metrics, balancing physiological accuracy and computational efficiency.
• Lead the end-to-end algorithm development cycle: from signal cleaning and feature extraction to modeling and validation while integrating code blocks into internal research pipelines and prototype environments, with a path toward production scalability.
• Work closely with hardware, firmware, and sensor teams to understand the physical signal path and improve the end-to-end sensing system.
• Explore the interplay between signal processing and machine learning to advance hybrid models for health sensing.
• Contribute to strategic roadmap planning for sensing innovation at Oura through data-driven insight and physiological domain expertise.

Requirements

• Bring 5+ years of experience in biosignal processing, with a strong focus on PPG, spectroscopy, or other physiological signals.
• Have a proven track record of applying signal processing techniques to real-world, noisy datasets—especially in wearable or remote monitoring environments.
• Possess strong coding skills in Python and experience with scientific computing libraries (e.g., NumPy, SciPy, pandas, matplotlib).
• Have an advanced degree (PhD or Master’s) in Biomedical Engineering, Electrical Engineering, Signal Processing, or a related field—or equivalent practical experience.
• Are familiar with techniques to manage motion artifacts, low SNR, and physiological variability in wearable systems.