Gnani.ai

NLP Intern

InternshipHybridJabalpur, Madhya Pradesh2 months34K/mo1 openingImmediate / Rolling

About this internship

Join Gnani.ai in Jabalpur as a NLP Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on natural language processing work. About the role As a NLP Intern at Gnani.ai, your core focus will be building text…

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Skills you'll use

PythonNatural Language ProcessingspaCyTransformersText ClassificationNamed Entity RecognitionTokenisationPyTorchData AnnotationModel Evaluation

What you'll do

Work on building text classification, extraction and conversational models alongside the core team
Apply Python, Natural Language Processing, spaCy, Transformers 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/MCA/M.Sc (CS, Linguistics, AI) — 2026 freshers & final-year students welcome
Working knowledge of Python, Natural Language Processing, spaCy (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 Jabalpur, Madhya Pradesh

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:

1Application screening & resume shortlisting by the talent team
2Discussion with the hiring manager on the role and your fit

About Gnani.ai

Gnani.ai operates in the artificial intelligence sector and has an active presence in Jabalpur. 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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