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.

💼 Work With Me

I currently teach a course on Improving LLM Applications With Evals.

If you need more hands-on help, I’m open to new consulting work and other forms of advisory. If you need help with your project, you can find more information here.

📮 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
1/19/25 Thoughts On A Month With Devin
12/13/24 nbsanity - Share Notebooks as Polished Web Pages in Seconds
11/30/24 Building an Audience Through Technical Writing: Strategies and Mistakes
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
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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