I am a machine learning engineer with over 20 years of experience. I have worked with innovative companies such as Airbnb and GitHub, which included early LLM research used by OpenAI, for code understanding. I have also led and contributed to numerous popular open-source machine-learning tools. I am currently an independent consultant helping companies operationalize Large Language Models (LLMs) to accelerate their AI product journey.

💼 Get In Touch

Do you need help operationalizing large language models? I’m open to new consulting work and other forms of advisory. If you need help with your project, send me a brief email at [email protected]

📮 Feed

I often share my experience building AI products. Below is a selected assortment of my longer-form writing on my machine learning work.

Date Title
10/29/24 Creating a LLM-as-a-Judge That Drives Business Results
10/10/24 Concurrency Foundations For FastHTML
7/29/24 An Open Course on LLMs, Led by Practitioners
6/1/24 What We’ve Learned From A Year of Building with LLMs
4/12/24 Debugging AI With Adversarial Validation
3/29/24 Your AI Product Needs Evals
3/27/24 Is Fine-Tuning Still Valuable?
2/14/24 Fuck You, Show Me The Prompt.
1/11/24 How To Debug Axolotl
1/9/24 Dokku: my favorite personal serverless platform
12/17/23 Tokenization Gotchas
11/15/23 Tools for curating LLM Data
10/28/23 vLLM & Large Models
10/15/23 Optimizing LLM latency
5/30/23 On commercializing nbdev
1/16/23 Why Should ML Engineers Learn Kubernetes?
7/28/22 nbdev Quarto: A new secret weapon for productivity
2/9/22 Notebooks in production with Metaflow
12/18/20 ghapi, a new third-party Python client for the GitHub API
11/20/20 Nbdev: A literate programming environment that democratizes software engineering best practices
9/1/20 fastcore: An Underrated Python Library
9/1/20 Data Science Meets Devops: MLOps with Jupyter, Git, & Kubernetes
3/6/20 GitHub Actions: Providing Data Scientists With New Superpowers.
2/21/20 Introducing fastpages, An easy to use blogging platform with extra features for Jupyter Notebooks.
2/5/20 Python Concurrency: The Tricky Bits
9/20/19 CodeSearchNet Challenge: Evaluating the State of Semantic Code Search
4/10/19 How to Automate Tasks on GitHub With Machine Learning for Fun and Profit
5/29/18 How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning
1/18/18 How To Create Magical Data Products Using Sequence-to-Sequence Models
12/16/17 How Docker Can Help You Become A More Effective Data Scientist
5/10/17 Automated Machine Learning — A Paradigm Shift That Accelerates Data Scientist Productivity @ Airbnb
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