Capability · Internships

B.Tech CSE (AI & ML) internships for B.Tech students in Delhi

B.Tech CSE (AI & ML) internships go to students who can show working code, not just a transcript. For B.Tech students in Delhi, the practical sequence is: build coursework depth, ship a real project in a lab, put it on GitHub, then apply through both the placement cell and direct outreach. At Vivekananda School of Engineering & Technology (VSET) at VIPS-TC Pitampura, the coursework side is a dedicated B.Tech track — B.Tech CSE (AI & ML), with project work running through the AICTE IDEA Lab.

At a glance

Topic
B.Tech CSE (AI & ML)
VSET programme
B.Tech CSE (AI & ML)
Coverage at VSET
Dedicated B.Tech track
Affiliation
GGSIPU (IP University), Delhi
Accreditation
NAAC A++ (VIPS-TC institutional)

What students actually build

  • Documented capstones include retrieval-augmented generation systems built over VIPS-TC corpora and multi-agent orchestrators.
  • Students enter Smart India Hackathon, where AI problem statements map directly onto this coursework.

How VSET teaches B.Tech CSE (AI & ML)

B.Tech CSE (AI & ML) is a four-year degree that builds machine learning, deep learning and LLM engineering on top of the computer science core. It is one of the seven GGSIPU-affiliated B.Tech programmes VSET runs at its Pitampura, Delhi campus, and the specialisation that leans hardest towards model training and agent systems. At VSET this maps to a dedicated B.Tech track — B.Tech CSE (AI & ML).

  • VSET offers B.Tech CSE (AI & ML) as a dedicated GGSIPU-affiliated specialisation, not an elective bolted onto general CSE.
  • The documented AI curriculum covers transformers, deep learning, reinforcement learning, computer vision, NLP and LoRA/QLoRA fine-tuning.
  • Agent and LLM engineering are taught explicitly, through a 160+ page Model Context Protocol library, a roughly 100 page agent-protocols library, and frameworks including LangChain, LangGraph, LlamaIndex, CrewAI and AutoGen.
  • Retrieval-augmented generation, vector databases and prompt engineering sit inside the same specialisation.
  • The full CSE core in programming, data structures, databases, operating systems and networks is taught before and alongside the AI subjects.

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 B.Tech CSE (AI & ML) skills lead

Graduates applying B.Tech CSE (AI & ML) skills typically target roles such as Machine Learning Engineer, LLM Engineer, AI Agent Developer, Computer Vision Engineer, Applied Research Engineer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.

Frequently asked questions

When should I start applying for B.Tech CSE (AI & ML) internships?

Most students target the summer after second or third year. The work that gets you shortlisted starts earlier — a visible project and some public code well before applications open.

What do B.Tech CSE (AI & ML) internship recruiters actually look at?

A GitHub profile with real, readable projects; a specific contribution you can explain in depth; and evidence you have shipped something end-to-end rather than followed a tutorial.

Is AI & ML a full branch at VSET or just an elective?

It is a dedicated GGSIPU-affiliated B.Tech specialisation, one of the seven programmes VSET runs, with AI coursework running through the degree rather than a single elective.

Does the AI & ML track cover LLMs and agents, or only classical machine learning?

Both. Alongside transformers, deep learning and reinforcement learning, the documented curriculum includes a 160+ page Model Context Protocol library, a roughly 100 page agent-protocols library, and LangChain, LangGraph, LlamaIndex, CrewAI and AutoGen.

Where do students train and fine-tune models on campus?

On the AICTE IDEA Lab GPU workstations, which support the LoRA and QLoRA fine-tuning work in the syllabus.

Sources

  1. VSET — Artificial Intelligence department — accessed 2026-08-31
  2. VSET — B.Tech CSE (AI & ML) — accessed 2026-08-31
  3. GGSIPU — IP University — accessed 2026-08-31