Fractal Analytics

Computer Vision Intern

InternshipIn OfficeChennai, Tamil Nadu3 months32K/mo3 openingsImmediate / Rolling

About this internship

Fractal Analytics has an open Computer Vision Intern position in Chennai 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 Fractal…

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 Chennai, Tamil Nadu

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 Fractal Analytics

Fractal Analytics operates in the artificial intelligence sector and has an active presence in Chennai. 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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