Optical Character Recognition internships for B.Tech students in Delhi

What students actually build

• Document-processing capstones use OCR as the ingestion stage of a RAG pipeline over real documents.
• Applied computer vision tools are a named capstone category at VSET.

How VSET teaches Optical Character Recognition

OCR converts text inside images and scanned documents into machine-readable characters, dealing with layout, skew, handwriting and poor scans. It is the ingestion step for almost every document-AI pipeline. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• OCR sits inside the computer vision material published at learn.engineering.vips.edu.
• It connects directly to the RAG and retrieval content, since scanned documents have to become text before they can be chunked and embedded.
• The deep learning material covers the recognition models modern OCR relies on.
• Delivered inside the B.Tech CSE (AI & ML) track, one of VSET's seven GGSIPU-affiliated B.Tech programmes.

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 Optical Character Recognition skills lead

Graduates applying Optical Character Recognition skills typically target roles such as Computer Vision Engineer, AI Engineer, Document AI Engineer, Machine Learning Engineer, Applied AI Developer. Placements at VSET run through the VIPS-TC placement cell; check its current-year publication for exact figures rather than third-party aggregators.