CommerceIQ

NLP / Generative AI Intern

InternshipIn OfficeBicholim, Goa3 months21K/mo2 openingsImmediate / Rolling

About this internship

Join CommerceIQ in Bicholim as a NLP / Generative AI Intern. This entry-level internship is designed for students and recent graduates who learn best by building, shipping and getting real feedback on applied AI and machine learning work. About the role As a NLP / Generative AI Intern at…

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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 Bicholim, Goa

Perks & benefits

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

Interview & selection process

4 rounds — typical selection flow for this role:

1Application screening & resume shortlisting by the talent team
2Practical assignment or case study with a short walkthrough
3Discussion with the hiring manager on the role and your fit
4HR discussion — stipend, start date, expectations and offer

About CommerceIQ

CommerceIQ operates in the saas / e-commerce analytics sector and has an active presence in Bicholim. 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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