AI/ML Research Internship

What You'll Do

• Work on AI/ML problems in sleep fitness and personal health.
• Scope problems, build end-to-end prototypes, validate with data, iterate toward shippable solutions.
• Receive hands-on mentorship and present results to leadership.
• Potentially develop work into publications.

Example topics:

• Multimodal Activity Understanding: Build and fine-tune vision- and physiology- foundation model for activity detection from wearables, Pod signals, and phone context.
• Next-Gen Time-Series Forecasting for Sleep: Multivariate forecasting for sleep stages, heart rate, HRV, recovery.
• Lifestyle-to-Sleep Simulation (“Digital Twin”): Simulator for lifestyle impacts on sleep.
• Adaptive Pod Thermoregulation: Personalized cooling/heating policies.
• Privacy-Preserving Personalization: Federated fine-tuning with differential privacy.

Minimum Qualifications

• Working toward undergraduate, graduate, or doctoral degree in computer science, engineering, data science, applied mathematics, or equivalent (doctoral preferred for research-focused).

Preferred Qualifications

• Proficiency with Python, Swift, Objective-C, or Java.
• Experience with TensorFlow, PyTorch, CoreFlow, Sklearn.
• Knowledge of ML algorithms, time series analysis, multimodal sensing, foundation model fine-tuning, reinforcement learning.
• Strong linear algebra and statistics.
• Collaboration and problem-solving skills.
• For Applied ML Engineering: Production integration, user studies, experiments.
• For Research-Focused: Doctoral pursuit, ML research publications.

Benefits

• Equity participation with refreshments.
• Pod product.
• Health, vision, dental insurance.
• Flexible PTO, commuter benefits, paid parental leave.