Notion

Computer Vision Intern

InternshipIn OfficeMapusa, Goa3 months24K/mo2 openingsImmediate / Rolling

About this internship

Notion has an open Computer Vision Intern position in Mapusa for motivated freshers and final-year students. You will work on live applied AI and machine learning projects and finish with something you can genuinely talk about in interviews. About the role As a Computer Vision Intern at Notion…

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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 Mapusa, Goa

Perks & benefits

Networking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentorLive project experience

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 Notion

Notion operates in the productivity saas (mnc) sector and has an active presence in Mapusa. 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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