David Leen is a senior software engineer with 13 years of experience building production-grade distributed systems and ML tooling, currently focused on developer-facing infrastructure at Netflix after a long tenure at AWS. He led SageMaker Notebooks and Studio launches, built remote Jupyter kernel infrastructure, and shipped scalable ML services including Comprehend document classification and a high-performance LDA algorithm. Comfortable bridging research and production, he has a strong applied-math background from Trinity College and the University of Washington and has driven teams from prototype to keynote-ready releases. An active open-source contributor, he has improved nbdev’s robustness for notebook-driven development—bringing practical improvements to the tools data scientists actually use.
13 years of coding experience
12 years of employment as a software developer
PhD (dropped out) Applied Mathematics, PhD (dropped out) Applied Mathematics at University of Washington
M.Sc. Theoretical Physics, M.Sc. Theoretical Physics at Trinity College Dublin
Contributions:7 reviews, 15 commits, 22 PRs in 2 months
Contributions summary:David primarily focused on improving the `nbdev` library's functionality and robustness. Their contributions included adding early returns to address performance issues, allowing for the preservation of metadata keys during cleaning, and fixing a bug related to non-notebook file handling. They also addressed an import issue and implemented enhancements to the Jupyter hooks, specifically reading settings.ini from the correct location and allowing for the specification of ports for preview.
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