Book list
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Short list on purpose. If I would not lend you my own copy, it is not here. Links go to Amazon and to the publisher where they sell direct. I get nothing from any of them.
Coding
- Cracking the Coding Interview by Gayle Laakmann McDowell. Still the best first book. Read the chapters on behavioural questions too, most people skip them and it shows. Amazon
- Grokking Algorithms by Aditya Bhargava. Pictures on every page. If the lessons in my coding track work for you, this is the same idea done by a better illustrator. Amazon · Manning
- Elements of Programming Interviews in Python by Aziz, Lee and Prakash. Harder than Cracking. Do this one second. Amazon
- Introduction to Algorithms by Cormen, Leiserson, Rivest and Stein. You do not read this cover to cover. You keep it on the desk and open it when a problem smells like a graph. Amazon
Systems
- Designing Data-Intensive Applications by Martin Kleppmann. If you read one book on this list, read this one. Twice. Amazon · O’Reilly
- System Design Interview, Volumes 1 and 2 by Alex Xu. The closest thing to a script for the design round. Learn the script, then throw it away. Volume 1 on Amazon · Volume 2 on Amazon · ByteByteGo
- Understanding Distributed Systems by Roberto Vitillo. Short, modern, and honest about what is hard. Amazon · Author’s site
- Site Reliability Engineering by Google. Free online. The chapters on SLOs and on-call are the ones interviewers quote back at you. Free at sre.google · Amazon
Staff level
- The Staff Engineer’s Path by Tanya Reilly. What the job actually is once nobody tells you what to do any more. Amazon · O’Reilly
- Staff Engineer by Will Larson. Shorter than Reilly, with interviews from people doing the job. The website has most of it for free. Amazon · staffeng.com
- The Pragmatic Programmer by David Thomas and Andrew Hunt. Twenty years old and still the book I wish every new hire had read. Amazon
GPU and AI
- Programming Massively Parallel Processors by Hwu, Kirk and Hajj. The only book that explains what a GPU is doing at the level an infrastructure engineer needs. Amazon
- Designing Machine Learning Systems by Chip Huyen. The systems view of ML, not the maths view. Amazon · O’Reilly
- AI Engineering by Chip Huyen. Her follow-up for the LLM era: serving, evaluation, inference cost. Pairs with my KV cache lesson. Amazon · O’Reilly
Free and worth your time
- NVIDIA NCCL documentation. Read the collectives chapter before any GPU infrastructure interview.
- The Complete NCCL Reference Guide and Attention Is All You Need: An Infrastructure Engineer’s Guide, two of my own posts that the GPU lessons here lean on.