Toddle

Computer Vision Intern

InternshipWork from HomeVellore, Tamil Nadu4 months20K/mo1 openingImmediate / Rolling

About this internship

Start your career in applied AI and machine learning with Toddle as a Computer Vision Intern in Vellore. 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 Toddle, your core focus…

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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 Vellore, Tamil Nadu

Perks & benefits

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

Interview & selection process

4 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Online aptitude / domain assessment
3Technical interview on fundamentals and your projects
4HR discussion — stipend, start date, expectations and offer

About Toddle

Toddle operates in the edtech (saas) sector and has an active presence in Vellore. 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…

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