Mad Street Den

Computer Vision Intern

InternshipIn OfficeJamshedpur, Jharkhand3 months43K/mo3 openingsImmediate / Rolling

About this internship

Start your career in computer vision with Mad Street Den as a Computer Vision Intern in Jamshedpur. You will sit with a working team, use the same tools and systems they do, and own a defined piece of work from day one. About the role As a Computer Vision Intern at Mad Street Den, your core focus…

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 Jamshedpur, Jharkhand

Perks & benefits

Pre-Placement Offer (PPO) opportunityFlexible working hoursNetworking with senior professionalsInternship CertificateLetter of Recommendation

Interview & selection process

2 rounds — typical selection flow for this role:

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

About Mad Street Den

Mad Street Den operates in the artificial intelligence sector and has an active presence in Jamshedpur. 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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