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InVideo

Computer Vision Intern

InternshipIn OfficeBengaluru, Karnataka3 months27K/mo3 openingsImmediate / Rolling

About this internship

InVideo has an open Computer Vision Intern position in Bengaluru 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 InVideo, your core…

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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 Bengaluru, Karnataka

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:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Technical interview on fundamentals and your projects

About InVideo

InVideo operates in the ai video & creator tech sector and has an active presence in Bengaluru. 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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