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Wadhwani AI

Computer Vision Intern

InternshipIn OfficeIndore, Madhya Pradesh3 months46K/mo2 openingsImmediate / Rolling

About this internship

Wadhwani AI has an open Computer Vision Intern position in Indore for motivated freshers and final-year students. You will work on live computer vision projects and finish with something you can genuinely talk about in interviews. About the role As a Computer Vision Intern at Wadhwani AI, your…

Skills you'll use

PythonComputer VisionOpenCVPyTorchCNNsObject DetectionImage SegmentationData AugmentationModel OptimisationNumPy

What you'll do

  • Work on building image and video models for detection and recognition alongside the core team
  • Apply Python, Computer Vision, OpenCV, 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/M.Sc (CS, Electronics) — 2026 freshers & final-year students welcome
  • Working knowledge of Python, Computer Vision, OpenCV (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 Indore, Madhya Pradesh

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. 2Online aptitude / domain assessment

About Wadhwani AI

Wadhwani AI operates in the artificial intelligence sector and has an active presence in Indore. 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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