LLM engineer roadmap 2026 — from ML practitioner to production
KDnuggets maps the skill progression from machine learning to shipping LLM applications at scale.
• Foundation: deep learning basics, transformers, attention mechanisms
• Practical: fine-tuning, retrieval-augmented generation (RAG), prompt engineering
• Production: inference optimization, cost control, monitoring in the wild
• Systems: serving, caching, latency, multi-model orchestration