upGrad

NLP / Generative AI Intern

InternshipIn OfficeSiliguri, West Bengal2 months22K/mo1 openingImmediate / Rolling

About this internship

Start your career in applied AI and machine learning with upGrad as a NLP / Generative AI Intern in Siliguri. 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 NLP / Generative AI Intern at upGrad, your core…

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Skills you'll use

PythonNLPTransformersHugging FaceText PreprocessingPyTorchModel EvaluationTokenisationGitEmbeddings

What you'll do

Work on training, evaluating and deploying models alongside the core team
Apply Python, NLP, Transformers, Hugging Face 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 Python, NLP, Transformers (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 Siliguri, West Bengal

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
2Technical interview on fundamentals and your projects
3Practical assignment or case study with a short walkthrough
4HR discussion — stipend, start date, expectations and offer

About upGrad

upGrad operates in the edtech sector and has an active presence in Siliguri. 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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