Eight Sleep

AI Research Intern

InternshipIn OfficeRanchi, Jharkhand6 months44K/mo3 openingsImmediate / Rolling

About this internship

Eight Sleep has an open AI Research Intern position in Ranchi for motivated freshers and final-year students. You will work on live AI research and algorithm design projects and finish with something you can genuinely talk about in interviews. About the role As an AI Research Intern at Eight…

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Skills you'll use

Algorithm DesignDeep LearningPyTorchAI EthicsAcademic Writing & PublishingLiterature ReviewExperiment DesignPythonMathematics for MLReproducible Research

What you'll do

Work on running structured experiments against open research problems alongside the core team
Apply Algorithm Design, Deep Learning, PyTorch, AI Ethics to live, production-facing problems
Document your work clearly for reviewers and stakeholders
Participate in reviews and act on the feedback you receive
Collaborate across engineering, product, design or business as required
Follow the team's quality, testing and documentation standards

Who can apply

Pursuing or recently completed B.E./B.Tech, M.Tech, M.Sc (CS / Mathematics) or Ph.D. scholars — 2026 freshers & final-year students welcome
Working knowledge of Algorithm Design, Deep Learning, PyTorch (or a genuine willingness to learn them)
Strong fundamentals in your discipline and clear problem-solving ability
Care with detail and the discipline to document your work
Clear written and verbal communication in English
Based in or willing to work from Ranchi, Jharkhand

Perks & benefits

Live project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionals

Interview & selection process

2 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Online aptitude / domain assessment

About Eight Sleep

Eight Sleep operates in the sleep health technology sector and has an active presence in Ranchi. Interns here are put on real work from the start, because the team's view is that the fastest way to learn a craft is to practise it under people who already do it well — not to watch it from a…

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