Observe.AI

NLP Intern

InternshipHybridBengaluru, Karnataka3 months33K/mo2 openingsImmediate / Rolling

About this internship

Join Observe.AI in Bengaluru 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 Observe.AI, your core focus will be building…

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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 Bengaluru, Karnataka

Perks & benefits

Flexible working hoursNetworking with senior professionalsInternship CertificateLetter of RecommendationMentorship from a named mentor

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 Observe.AI

Observe.AI operates in the artificial intelligence sector and has an active presence in Bengaluru. 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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