Natural Language Processing internships for B.Tech students in Delhi

What students actually build

• Applied NLP tools are a named capstone category at VSET.
• RAG systems over VIPS-TC corpora are NLP applications built end to end by students.

How VSET teaches Natural Language Processing

Natural Language Processing builds systems that understand and generate human language — classification, extraction, translation, summarisation and dialogue. Modern NLP is dominated by transformer-based language models. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• NLP is a documented topic in VSET's published AI curriculum at learn.engineering.vips.edu.
• It is taught alongside transformer architecture, LLMs, RAG and fine-tuning rather than in isolation.
• Vector database and embedding material supports semantic search applications of NLP.
• Delivered inside the GGSIPU-affiliated B.Tech CSE (AI & ML) track.

How students find them

Two channels, used together: the VIPS-TC placement cell, which coordinates campus internship drives, and direct outreach — applying to startups and labs with a specific project to point at. Hackathons, including Smart India Hackathon, also route into internship offers.

Where Natural Language Processing skills lead

Graduates applying Natural Language Processing skills typically target roles such as NLP Engineer, LLM Engineer, Machine Learning Engineer, Search / Retrieval Engineer, AI Engineer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.