
Machine Learning Scientist – Summer Intern
ŌURA
internship
Posted on:
Location Type: Remote
Location: Alaska • Iowa • United States
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Salary
💰 $106,250 - $125,000 per year
Job Level
About the role
- Work closely with experienced scientists and engineers on real research and product-facing problems
- Contribute to analyses, models, and scientific insights that directly impact Oura members
Requirements
- Ongoing studies in a STEM field such as biomedical engineering, computer science, electrical engineering, applied mathematics, statistics, neuroscience, or a related discipline
- Strong Python skills and experience working with scientific or ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, or similar).
- A foundational understanding of human physiology, particularly as it relates to wearable signals (e.g., cardiovascular function, autonomic nervous system, sleep, thermoregulation, or movement).
- Experience or coursework in signal processing and/or machine learning, especially for time-series data.
- Clear written and verbal communication skills, with the ability to explain technical results to a multidisciplinary audience.
- Comfort working independently in a remote environment while collaborating closely with a distributed team.
- Nice to have: familiarity with cloud-based data or ML workflows (e.g., AWS, databases, data pipelines).
- Nice to have: interest in foundation models, fine-tuning them and working with time series embeddings.
Benefits
- Competitive salary
- Health, dental, vision insurance, and mental health resources
- An Oura Ring of your own plus employee discounts for friends & family
- 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off *prorated
- Paid sick leave
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonNumPypandasscikit-learnPyTorchsignal processingmachine learningtime-series datadata pipelinesfine-tuning
Soft Skills
clear communicationwritten communicationverbal communicationindependent workcollaboration