Machine Learning Research Scientist; Health & Sensing

Requirements

• We are seeking someone who is passionate about health technologies and about making an impact on health outcome
• We look for people who tackle problems with a system approach, and make data driven decisions to deliver the best products to our users
• 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)

• Eight Sleep is the first sleep fitness company. At Eight Sleep we design products at the forefront of sleep innovation
• Our mission is to make people’s sleep count for more, using innovative technology, minimalistic design, and proven clinical science to personalize and improve each night for everybody—changing the way people sleep forever and for better
• 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