LLM Systems Engineering: Training and Building Large Language Models – Engineering AI Models Through Fine-Tuning, Continued Pretraining, and From-Scratch Development (AI Engineering)

LLMs are highly general purpose technology for statistical modeling of token streams… If you can reduce your problem to that of modeling token streams, you can 'throw an LLM at it.'
– Andrej Karpathy, founding member of OpenAI

Large language models have become the defining technology of the current decade , powering tools that write and reason at scale. However, there is much more to LLMs than just the chat interface of ChatGPT or Claude: a deeper opportunity to design and adapt models to your own specific needs.

Research scientist and author Rob McKinsey presents a detailed resource on the topic, spanning 42 modules organized into eight major chapters. The discussion begins with the inner workings of an LLM and progresses to data engineering and training production models with Python and modern engineering tools.

Main Topics
• How tokens, embeddings, and the transformer architecture turn text into model behavior
• How pretraining objectives and inference loops actually work
• How to plan data and compute budgets for an LLM project
• How to fine-tune, continue pretraining, and train from scratch with Python and Unsloth

Features
• Detailed code examples
• 60+ visualizations and figures
• 170+ primary research citations

Who This Book Is For
This book is written for developers, AI architects, and enthusiasts who want a deeper, foundational understanding of how large language models are composed and trained. It assumes comfort with general programming and basic ideas from linear algebra and probability. The material is presented at an intermediate to advanced level.

Table of Contents
• Chapter I – Introduction to Large Language Models
• Chapter II – Strategic and Technical Planning
• Chapter III – Data Engineering
• Chapter IV – Training Systems and Model Development
• Chapter V – Fine-Tuning
• Chapter VI – Continued Pretraining
• Chapter VII – Training from Scratch
• Chapter VIII – Evaluation, Monitoring, and Maintenance

Whether you are learning the fundamentals of LLM systems or training and adapting models in professional environments, this book provides a structured and practical guide to understanding and designing language models that perform reliably across real-world workflows.

Scroll up and click Buy Now to start reading.