Senior ML Algorithm Scientist

Job description

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 millions of 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. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office. We are seeking a Senior ML Algorithm Scientist to join our Future Physiology team. This is a high-impact opportunity for a deeply technical, hands-on expert who thrives in fusing physiology, machine learning, and real-world biosignal R&D. You will play a pivotal role in advancing Oura’s next generation of features, turning noisy, multimodal data from sensors (like PPG, motion, and temperature) into reliable, scalable, and productizable health metrics that reach millions of users. What You Will Do: Take responsibility for the entire ML and algorithm development pipeline, from signal processing to training, evaluating, and scaling robust models. Develop and deploy advanced ML algorithms leveraging deep learning architectures (e.g., Transformers, RNNs, probabilistic models) alongside classical signal processing to derive meaningful health insights across diverse populations. Design robust methods for fusing time-series data from multiple sensors (e.g., PPG, motion, temperature, spectroscopy) to extract reliable physiological metrics while managing everyday issues like motion artifacts. Leverage Oura’s large-scale cloud datasets to refine models, while also working hands-on with prototype sensors and evaluation kits to see how new hardware performs in the real world. Work directly with hardware, firmware, software, and data infrastructure teams to align on feature goals, ensure technical feasibility within the ring's physical limits, and smoothly integrate algorithms. Translate complex technical concepts and your technical results into clear narratives for senior stakeholders, helping to guide our future research direction and roadmap alignment. This is a role in London, UK. Travelling to US and Finland might be required. What you'll bring: 5–7+ years of experience in machine learning, biosignal processing, sensor fusion, and analyzing real-world, multimodal time-series data. Deep proficiency in Python, practical experience with tools like PyTorch or TensorFlow, and scientific computing libraries (NumPy, SciPy, pandas, matplotlib). A strong understanding of the physiology underlying the signals. You need to know what the data actually represents physically, combined with the engineering intuition to solve complex, noisy problems. Familiarity with scalable data systems and a track record of getting ML models out of the lab and into production. An advanced degree (Master’s or PhD) in Computer Science, Machine Learning, Biomedical Engineering, Signal Processing, Applied Math, or a related field (or equivalent practical experience). Comfortable navigating uncertainty and fast-paced iteration, taking complete accountability for the algorithm journey from early feasibility testing to production-ready integration. Nice to have: Direct experience working with consumer health products, wearable sensors, smart rings, or digital health applications. Benefits: At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health and add to our benefits! What we offer: Competitive salary An Oura Ring of your own + employee discounts for friends & family Flexible working hours and remote working arrangements Amazing culture of collaborative and passionate coworkers If this sounds like the next step for you, please send us your application and CV as soon as pos