AI Safety internships for B.Tech students in Delhi

What students actually build

• Evaluation and guardrail design form part of the RAG, agent and fine-tuning capstones students build.
• Safety constraints matter directly in the MCP servers students write, which define what tools a model may call.

How VSET teaches AI Safety

AI safety is the study of making AI systems behave reliably and within intended limits — covering alignment, robustness, misuse resistance and failure analysis. In LLM systems it spans training-time alignment and deployment-time guardrails. At VSET this maps to documented coursework depth inside B.Tech CSE (AI & ML).

• AI safety is a named topic in VSET's published AI curriculum at learn.engineering.vips.edu.
• It is taught alongside RLHF, which is the main production mechanism for aligning model behaviour.
• Agent-protocol and MCP material covers the tool-access boundaries that constrain autonomous systems.
• Delivered inside the GGSIPU-affiliated B.Tech CSE (AI & ML) track at VSET.

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 AI Safety skills lead

Graduates applying AI Safety skills typically target roles such as AI Safety Engineer, ML Engineer (Evaluation), AI Research Associate, Responsible AI Analyst, 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.