ML Research Scientist (Health & Sensing)
Develops AI/ML models to transform sensor data into personalized health and sleep insights, focusing on thermoregulation, foundation models, and behavioral simulations using vast sleep datasets. Requires PhD in ML/AI-related field, 3+ years practical ML experience, and strong publications.
About the job
How you'll contribute
Example projects include:
- Autopilot Thermoregulation: Advance the Pod's adaptive thermoregulation system - the "autopilot" system that continuously learns and reacts to micro-events like restlessness or awakenings. Design policies that optimize comfort and sleep quality in real time through reinforcement learning and closed-loop control.
- Health Foundation Modeling: Develop a multimodal health foundation model that integrates physiology and environmental context - learning from Pod signals, wearable sensors, and contextual data - powered by one billion+ hours of sleep data at Eight Sleep.
- Behavioral simulations: Build a high-fidelity physiological simulator that models how daily behaviors ripple into tonight's sleep and tomorrow's readiness. This initiative aims to create a non-invasive, always-on model of healthy aging powered by Pod biosignals and continuous physiological data.
What you'll need to succeed
- Expertise in at least one area of machine learning and artificial intelligence (e.g., self-supervised learning, multi-modal ML, model optimization, NLP, LLM)
- Strong interest in applying machine learning to health related problems and data
- Experience using a programming language (Python, C/C++ etc.) to manipulate data, draw insights from large data sets, and train machine learning models
- 3+ years of practical experience applying ML to solve real-world problems or relevant quantitative and qualitative research and analytics experience
- PhD in Computer Science, Machine Learning, AI, Statistics, Mathematics, or related quantitative field with a notable publication record; or BS/MS with publications at top venues (e.g. NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ACL, EMNLP, INTERSPEECH)
Skills
Machine Learning, Self-Supervised Learning, Multi-Modal Ml, Reinforcement Learning, Python, C++, NLP, LLMs, PyTorch, TensorFlow
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