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eInfochips

Research Intern (AI/ML)

InternshipIn OfficeNashik, Maharashtra6 months22K/mo3 openingsImmediate / Rolling

About this internship

eInfochips has an open Research Intern (AI/ML) position in Nashik for motivated freshers and final-year students. You will work on live applied AI and machine learning projects and finish with something you can genuinely talk about in interviews. About the role As a Research Intern (AI/ML) at…

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Skills you'll use

PythonDeep LearningLiterature ReviewPyTorchExperiment DesignStatisticsPaper WritingModel EvaluationGitReproducibility

What you'll do

  • Work on training, evaluating and deploying models alongside the core team
  • Apply Python, Deep Learning, Literature Review, PyTorch 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/MCA/M.Sc (CS, Statistics, Maths) — 2026 freshers & final-year students welcome
  • Working knowledge of Python, Deep Learning, Literature Review (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 Nashik, Maharashtra

Perks & benefits

Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experience

Interview & selection process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Discussion with the hiring manager on the role and your fit

About eInfochips

eInfochips operates in the product engineering sector and has an active presence in Nashik. 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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