AI/ML Research Internship

The Role

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.

What You'll Help Build

Example topics include:

• 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.

What You'll Need to Succeed

Minimum Qualifications

• 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.

Preferred Qualifications

It’s helpful if you meet one or more of the following qualifications, but it isn’t a requirement

• Proficiency with an object-oriented programming language, such as Python, Swift, Objective C or Java
• Experience with ML libraries, such as TensorFlow, PyTorch, CoreFlow, and Sklearn
• Practical knowledge related to building and adapting algorithms for machine learning, time series analysis, multimodal sensing, foundation model fine-tuning, reinforcement learning and related areas
• Familiarity with crafting, prototyping, and evaluating interactive systems
• Excellent mathematical skills in linear algebra and statistics
• Ability to collaborate with others
• Problem solving skills
• Applied ML Engineering internships: Experience with integrating research prototypes into production applications. Proficiency conducting ethnographic or other situated studies of human interaction with or through interactive technologies. Experience crafting, conducting, analyzing, and interpreting experiments and investigations
• Demonstrated expertise with proven publication or track record in at least one of the areas: machine learning, statistics, econometrics, operations research, quantitative marketing, causal inference, time series analysis, stochastic modeling, optimization and decision theory
• Research-Focused internships: Currently pursuing a doctoral degree. Research experience in Machine Learning and a demonstrable record of publishing academic research in peer-reviewed venues