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Emeritus

Computer Vision Intern

InternshipHybridJammu, Jammu & Kashmir2 months25K/mo4 openingsImmediate / Rolling

About this internship

Join Emeritus in Jammu as a Computer Vision Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on applied AI and machine learning work. About the role As a Computer Vision Intern at Emeritus, your core…

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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 Jammu, Jammu & Kashmir

Perks & benefits

Mentorship from a named mentorLive project experienceExposure to professional tools and workflowsPre-Placement Offer (PPO) opportunityFlexible working hours

Interview & selection process

2 rounds — typical selection flow for this role:

  1. 1Application screening & resume shortlisting by the talent team
  2. 2Team-fit / behavioural interview with the team

About Emeritus

Emeritus operates in the edtech sector and has an active presence in Jammu. 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 at…
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