What a LLM Engineering & Fine-Tuning intern does

The LLM Engineering & Fine-Tuning role, what you build at each level and what you need before you start.

Build real products on large language models: prompting, structured output, RAG over documents, tool calling, evaluation, LoRA fine-tuning of open models, quantization, serving and guardrails.

What you build, level by level

Level 1: Foundations: How LLMs work, Count tokens, First API call from Python and more.
Level 2: Building real features: Document chatbot (RAG), Chunking comparison, Hybrid search and re-ranking and more.
Level 3: Professional work and capstone: Serve your model, Quantization trade-off, Guardrails and more.

Where this work is used

Training Trains, W3AppDevelopers and DomainHostly use these skills in real projects: AI / Machine Learning Solutions. Interns who pass the readiness check can take paid-company work from the Company Work board in the portal.

Before you start

Basic Python is needed. Free Colab or Kaggle GPUs are enough for fine-tuning small models; no paid GPU is required.

Tools and first-week setup →