Intel

Computer Vision Intern

InternshipHybridPune, Maharashtra6 months27K/mo4 openingsImmediate / Rolling

About this internship

Intel is hiring a Computer Vision Intern in Pune — a hands-on, mentor-led internship built for students and 2026 freshers who want real exposure to applied AI and machine learning rather than a certificate-only programme. About the role As a Computer Vision Intern at Intel, your core focus will be…

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Skills you'll use

OpenCVPythonDeep LearningImage ProcessingPyTorchDataset AnnotationModel EvaluationNumPyGitCUDA Basics

What you'll do

Work on training, evaluating and deploying models alongside the core team
Apply OpenCV, Python, Deep Learning, Image Processing 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 OpenCV, Python, Deep Learning (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 Pune, Maharashtra

Perks & benefits

Internship CertificateLetter of RecommendationMentorship from a named mentorLive project experienceExposure to professional tools and workflows

Interview & selection process

4 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
3Team-fit / behavioural interview with the team
4HR discussion — stipend, start date, expectations and offer

About Intel

Intel operates in the semiconductors sector and has an active presence in Pune. 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 distance. The work runs…

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