Senior ML & Biosignal Scientist

We are seeking a Senior ML & Biosignal Scientist to join our Future Physiology team in Finland. This is a high-impact role for a deeply technical, hands-on expert who excels at bridging human physiology, machine learning, and real-world biosignal R&D. Working directly alongside our world-class hardware, firmware, software and science teams, you will play a pivotal role in shaping Oura’s next-generation features. You will turn noisy, multimodal sensor data (including PPG, motion, and temperature) into robust, scalable, and actionable health insights delivered to millions of members worldwide.

• →Take full technical ownership of the algorithm lifecycle, from physiological background and signal processing to model architecture design, evaluation, and scaling for production.
• →Develop and deploy state-of-the-art ML algorithms leveraging deep learning (e.g., Transformers, RNNs, probabilistic models) to extract meaningful physiological metrics across diverse user populations, effectively solving real-world challenges such as motion artifacts and environmental noise.
• →Leverage Oura’s large-scale cloud datasets and work hands-on with prototypes, hardware evaluation kits, and benchtop testing setups.
• →Translate complex algorithmic results and physiological insights into clear technical strategies and strategic narratives for senior leadership to help guide Oura’s future product roadmap.

This is a hybrid role out of our Oulu or Helsinki office.

• 5–7+ years of hands-on experience in machine learning, biosignal processing, sensor fusion, and analyzing real-world, multimodal time-series data.
• Expertise with modern ML frameworks (PyTorch) alongside the scientific computing stack (NumPy, SciPy, pandas, scikit-learn).
• Strong domain knowledge of human physiological systems underlying wearable biosignals, paired with the engineering intuition needed to extract clean signals from noisy data.
• Familiarity with modern data infrastructure, scalable cloud systems, and a proven track record of moving ML models from experimental research into production software.
• Master’s or PhD in Computer Science, Machine Learning, Biomedical Engineering, Signal Processing, Applied Mathematics, Physics, or a closely related field (or equivalent practical track record).
• Comfortable working in an agile environment with high autonomy, taking complete ownership of algorithm development from early-stage concept testing to deployment.

• Direct experience in consumer health tech, wearable hardware or digital health applications.
• Prior experience working within cross-disciplinary teams spanning software engineering, hardware development, and clinical research.