Senior ML & Biosignal Scientist

Job Description

Senior ML & Biosignal Scientist | Confidential Employer

The Tone:
This is a hybrid role at ŌURA, located in Oulu or Helsinki, Finland. ŌURA empowers people to gain a deeper knowledge of their readiness, activity, and sleep quality through the Oura Ring and its connected app. This high-impact Senior ML & Biosignal Scientist role plays a pivotal part in shaping ŌURA’s next-generation features. You will bridge human physiology, machine learning, and real-world biosignal R&D to deliver robust, scalable, and actionable health insights to millions of members worldwide.

The TL;DR
• Role: Full Time
• Location: Hybrid – Oulu or Helsinki
• Team: Future Physiology team
• Mission: To turn noisy, multimodal sensor data (including PPG, motion, and temperature) into robust, scalable, and actionable health insights for millions of members worldwide.
• Tech Stack: PyTorch, NumPy, SciPy, pandas, scikit-learn

What You’ll Actually Do
• Algorithm Ownership: Take full technical ownership of the algorithm lifecycle, spanning physiological background, signal processing, model architecture design, evaluation, and scaling for production.
• ML Development: 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.
• Data & Prototyping: Leverage ŌURA’s large-scale cloud datasets and work hands-on with prototypes, hardware evaluation kits, and benchtop testing setups.
• Strategic Communication: Translate complex algorithmic results and physiological insights into clear technical strategies and strategic narratives for senior leadership to help guide ŌURA’s future product roadmap.

The Must-Haves
• Background: 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). Strong domain knowledge of human physiological systems underlying wearable biosignals.
• Experience: 5–7+ years of hands-on experience in machine learning, biosignal processing, sensor fusion, and analyzing real-world, multimodal time-series data. Proven track record of moving ML models from experimental research into production software.
• Skills: Expertise with modern ML frameworks (PyTorch) alongside the scientific computing stack (NumPy, SciPy, pandas, scikit-learn). Familiarity with modern data infrastructure, scalable cloud systems, and engineering intuition needed to extract clean signals from noisy data.
• Bonus: 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.