Eight Sleep

Eight Sleep

AI/ML Research Internship

San Francisco · Intern · Internship

Sponsorship not specifiedDetected 288 days ago
PythonJavaSwiftReactObjective-CObject-Oriented ProgrammingAlgorithmsMachine LearningTensorFlowPyTorchscikit-learnData ScienceStatisticsForecastingAvidResearchCollaborationProblem SolvingMentoring

About 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.
  • Along the way, you'll receive hands-on mentorship, sharpen your technical toolkit, and present your results to leadership.
  • We're seeking interns who care about outcomes, think in systems, and make data-driven decisions.

Responsibilities

  • Every role at Eight Sleep is a chance to create cutting-edge technology, collaborate with world-class talent, and help shape a future where sleep isn't passive - it's a powerful tool for living better.
  • If you're tired of the ordinary and driven to build at the edge of what's possible, this is your moment.
  • Join us and lead the movement that's transforming how the world sleeps and what we're all capable of when we wake up.
  • We're here to build fast, push limits, and deliver without compromise.

Requirements

  • 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
  • Research-Focused internships: Currently pursuing a doctoral degree.

Nice to have

  • 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.
  • 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
  • Familiarity with crafting, prototyping, and evaluating interactive systems
  • Excellent mathematical skills in linear algebra and statistics
  • Problem solving skills

Compensation

  • Equitable compensation and continuous equity investment

Benefits

  • As the world's first sleep fitness company, we're redefining what it means to be well-rested and building the most advanced hardware, software, and AI technology to make it possible.
  • We are trusted by high performers, professional athletes, and health-conscious consumers in over 30 countries worldwide.
  • 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.
  • Equitable compensation and continuous equity investment
  • We extend equity participation to every full-time team member, recognizing and rewarding your direct contributions to our success.
  • This includes periodic equity refreshments based on performance, ensuring that as Eight Sleep grows and succeeds, so do you - perfectly aligning your achievements with the broader triumphs of the company.
  • Your own Pod - and other great benefits

Company info

  • Full access to health, vision, and dental insurance for you and your dependents
  • Supplemental life insurance
  • Flexible PTO
  • Commuter benefits to ease your daily commute
  • Paid parental leave
  • We operate with intensity because our mission demands it.
  • At Eight Sleep, we're on a mission to fuel human potential through optimal sleep.

Visa & Work Authorization

  • al employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status

This listing is sourced directly from Eight Sleep's careers page and normalized into a canonical job model.