Chip Huyen

Career

Chip Huyen describes the work as bringing AI into production and writing about AI system design. Huyen worked on ML tooling at NVIDIA as a core developer of NeMo, worked at Snorkel AI and Netflix, and founded an AI infrastructure company that was later sold.¹

At Stanford, Huyen was the instructor for CS 329S, a project-based course on machine learning systems design. The course page notes that its lecture notes were expanded into the book Designing Machine Learning Systems.²¹

Books

Huyen's book Machine Learning Interviews (2021) is free and open-source and is being folded into a broader AI engineering curriculum. Designing Machine Learning Systems (O'Reilly, 2022) takes a holistic view of ML system design, treating each decision in terms of the system's overall objectives, and has been translated into several languages.³⁴⁵

AI Engineering (O'Reilly, 2025) covers building applications on readily available foundation models, with a framework for developing and deploying them and guidance on models, datasets, evaluation benchmarks, and application patterns. Huyen has also written four books of stories in Vietnamese.³⁶¹

Open-source work and blog

Huyen builds small public tools, including GoodAIList for discovering open-source AI projects, KilledByGPT, and the lazynlp library for building large text datasets. Huyen's blog covers AI systems, with posts such as a 2024 survey of open-source AI tooling, a 2024 overview of the components of a generative AI platform, and a 2025 essay on agents.¹⁷⁸

Work and contributions

• NVIDIA NeMo Open-source code

  Huyen's homepage describes Huyen as a core developer of NeMo while working on ML tooling at NVIDIA. The NeMo repository is licensed under Apache 2.0.¹⁹

• Designing Machine Learning Systems (O'Reilly, 2022) Published research

  Author of the book, which expanded the lecture notes of the Stanford course CS 329S that Huyen taught.²¹

• AI Engineering (2025) Published research

  Author of the 2025 book on AI engineering, listed on Huyen's homepage.¹

• Machine Learning Interviews (2021) Published research

  Author of a free, open-source book on machine learning interviews, written for candidates and also used by hiring managers.³⁴

• lazynlp Open-source code

  Author of a library for scraping and cleaning web pages to build large text datasets.⁷¹

Timeline

1. Feb 2019Released lazynlp, a library to scrape and clean web pages for building text datasets.⁷
2. 2021Published Machine Learning Interviews as a free, open-source book.³⁴
3. 2022Published Designing Machine Learning Systems with O'Reilly, expanding the CS 329S lecture notes.³²⁵
4. Mar 14, 2024Published a survey of open-source AI tools built around foundation models.⁸
5. Jul 25, 2024Published Building A Generative AI Platform, an overview of the components of such platforms.⁸
6. 2025Published AI Engineering with O'Reilly, a book on building applications with foundation models.³⁶
7. Jan 7, 2025Published Agents, a long-form post on AI agents.⁸

Documented roles

The sources do not confirm a current role; these are the roles they document.

• ML tooling; core developer of NeMo, NVIDIA¹
• Instructor, CS 329S, Stanford University¹²
• Previously worked at the company, Snorkel AI¹
• Previously worked at the company, Netflix¹

Companies in their history

• NVIDIA 43 people in the wiki
• Stanford University 40 people in the wiki

Related people

• Bratin SahaConnected to NVIDIA
• Tim CostaConnected to NVIDIA
• Tianqi ChenConnected to NVIDIA
• Jonathan CohenConnected to NVIDIA
• Clément FarabetConnected to NVIDIA
• Andreas C. MüllerML frameworks and libraries · Developer tools
• William FalconML frameworks and libraries · Developer tools
• Piero MolinoML frameworks and libraries · Developer tools
• Logan KilpatrickTeaching and writing · Developer tools
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