Henry Ehrenberg is a co-founder and engineering leader with 11 years of experience building data-first machine learning platforms, currently spearheading product and engineering efforts at Snorkel AI in San Francisco. He bridges research and production, having worked on weak supervision and information extraction at Stanford's Hazy Research Group and led universal representation learning as a Senior Applied Research Scientist at Facebook. Technically fluent across back-end systems and databases, he contributed core parsers, document/sentence processing, and holdout evaluation features to the widely used open-source Snorkel project. His work also covers tooling and reproducibility—authoring notebook sync and verification scripts for Snorkel tutorials to ensure reliable onboarding and developer experience. Trained in applied mathematics at Yale and data science at Stanford, he combines rigorous academic foundations with pragmatic startup execution. A less obvious strength is his knack for improving developer workflows and testability, turning research ideas into maintainable engineering artifacts.
11 years of coding experience
5 years of employment as a software developer
Bachelor of Science (BS) Applied Mathematics, Bachelor of Science (BS) Applied Mathematics at Yale University
Master of Science (MS) Computational and Mathematical Engineering (Data Science track), Master of Science (MS) Computational and Mathematical Engineering (Data Science track) at Stanford University
A system for quickly generating training data with weak supervision
Role in this project:
Back-end Developer & Database Engineer
Contributions:3 releases, 17 reviews, 678 commits in 5 years 10 months
Contributions summary:Henry added generic code parsers and HTML parsers, fixing parser installation scripts and HTML parser issues. They also implemented features for document parsing and sentence processing, including methods for extracting sentences and text from parsed documents. Furthermore, the user added support for holdout capabilities, which are crucial for model evaluation and feature analysis.
Contributions:1 review, 52 commits, 96 PRs in 6 months
Contributions summary:Henry contributed to the initial setup and configuration of the tutorial repository, including adding instructions and addressing code formatting. Their work involved setting up essential components of the project. In addition, the user implemented functionalities for checking and syncing notebooks within the repository, including developing scripts for verifying notebook consistency. This indicates a focus on build processes and ensuring the integrity of the tutorial content.
snorkel
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