Generative AI internships for B.Tech students in Delhi

What students actually build

• Capstones include LoRA fine-tunes on open-weight models and RAG systems built over VIPS-TC corpora.
• Students also build MCP servers and LangGraph-based multi-agent orchestrators around generative models.

How VSET teaches Generative AI

Generative AI covers models that produce new content — text, images, audio or code — rather than only classifying existing data. Large language models and diffusion models are its two most visible families. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• Generative AI topics are documented in the open curriculum at learn.engineering.vips.edu, including transformers, fine-tuning and prompt engineering.
• Taught within the B.Tech CSE (AI & ML) track at VSET, affiliated to GGSIPU.
• The curriculum treats generative systems as engineering artefacts — retrieval, orchestration and evaluation — not just model theory.
• Related agent and protocol libraries (MCP, A2A) sit alongside the generative-model material.

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 Generative AI skills lead

Graduates applying Generative AI skills typically target roles such as Generative AI Engineer, LLM Application Developer, AI Engineer, Prompt Engineer, Applied Scientist. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.