Designing Machine Learning Systems
Background summary — AI-generated; not source-grounded.
About
Designing Machine Learning Systems (O’Reilly, 2022) by Chip Huyen covers the full lifecycle of production ML systems — from problem framing and data engineering through training, evaluation, deployment, and monitoring. The book addresses the gap between academic ML (optimising metrics on fixed datasets) and production ML (maintaining performance in changing real-world environments). Topics include feature engineering, training data management, model evaluation, deployment strategies, and ML infrastructure.
In the wiki
Mentioned by: Chip Huyen Episode: Chip Huyen on AI Engineering (Lenny’s Podcast, 2025)
Referenced as background for Chip’s expertise in the Chip Huyen on AI Engineering transcript. Precedes AI Engineering and focuses on the ML Engineering side of the AI Engineering / ML Engineering distinction.
See also
- Chip Huyen — author
- AI Engineering — Chip Huyen’s follow-up book
- AI Engineering — concept page
- Reinforcement Learning from Human Feedback