AI/ML Research Internship, Eight Sleep

• Working toward an undergraduate, graduate or doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent. Doctoral degree paths are preferred for research focused internships

Desirable

• Eight Sleep is looking for Machine Learning research interns to work on AI/ML problems in the sleep fitness and personal health space
• You’ll work closely with a cross-functional team to scope problems, build end-to-end prototypes, validate with data, and iterate toward something we can ship
• Along the way, you’ll receive hands-on mentorship, sharpen your technical toolkit, and present your results to leadership
• Where appropriate, you may also develop your work into a publication
• We’re seeking interns who care about outcomes, think in systems, and make data-driven decisions
• If you’re excited to learn fast, collaborate deeply, and deliver meaningful improvements for users, we’d love to work with you
• Multimodal Activity Understanding: Build and fine-tune a vision- and physiology- foundation model that detects daily activities (workouts, meals, naps) from wearables, Pod signals, and phone context to explain sleep trends
• Next-Gen Time-Series Forecasting for Sleep: Push state of the art on multivariate forecasting to predict sleep stages, heart rate, HRV, and recovery days ahead - robust to missing data and lifestyle shifts
• Lifestyle-to-Sleep Simulation (“Digital Twin”): Create a high-fidelity simulator that models how choices (caffeine, exercise timing, alcohol, travel) ripple into tonight’s sleep and tomorrow’s readiness
• Adaptive Pod Thermoregulation: Learn personalized cooling/heating policies that react to micro-events (restlessness, awakenings) in real time - balancing comfort, sleep continuity, and energy
• Privacy-Preserving Personalization: Train better models without centralizing raw data: federated fine-tuning with differential privacy for sleep staging, anomaly detection, and forecasting