Remote Machine Learning Scientist Intern

Description:

• Oura is seeking a talented and motivated Machine Learning Scientist Intern to join their Science team.
• The intern will help build next-generation machine learning algorithms focused on health insights.
• The role involves applying state-of-the-art deep learning and generative AI algorithms to extract novel health insights.
• Responsibilities include building large-scale machine learning pipelines on health data and delivering robust statistical analyses of machine learning models.
• The intern will document, summarize, and present data analysis and algorithm performance results with actionable recommendations for a broad audience.
• The internship lasts for 3-4 months, with flexible timing between June and September 2025.
• This is a remote role, preferably for candidates based on the East Coast or in Boston.

Requirements:

• Candidates should have completed all but the last year of their PhD/Master’s degree in machine learning, artificial intelligence, data science, computer science, biomedical engineering, electrical engineering, biostatistics, or a related field.
• Solid programming skills in Python and SQL are required.
• Experience with machine learning and deep learning, particularly with time-series or biosignal data, is necessary.
• A passion for machine learning and generative AI applications aimed at improving health is essential.
• Candidates must be self-driven, motivated, and able to work independently in a dynamic environment.
• Effective communication and collaborative skills are required, even in a remote setting.

Benefits:

• Oura offers a competitive salary and equity packages.
• Health, dental, vision insurance, and mental health resources are provided.
• Each employee receives an Oura Ring and discounts for friends and family.
• The position includes 20 days of paid time off, 13 paid holidays, and 8 days of flexible wellness time off.
• Paid sick leave and parental leave are also included.
• Oura takes a market-based approach to pay, with salary ranges varying by location and determined by job-related skills, experience, and market conditions.