AI/ML Research Internship
AI/ML research intern building prototypes for sleep fitness applications like multimodal activity understanding, time-series forecasting, and personalized thermoregulation. Works with cross-functional team on data-driven solutions; requires student status in CS/data science/ML-related field, prefers research experience and ML proficiency.
About the job
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.
Skills
Python, TensorFlow, PyTorch, scikit-learn, Machine Learning, Time Series Analysis, Foundation Models, Reinforcement Learning, Linear Algebra, Statistics
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