Francis Lam is a founder and seasoned engineering leader with 12 years of experience building platforms, data science teams, and production-grade back-end systems across startups and enterprise healthcare. He has held senior roles from VP Data Science to VP Platform and CTO, blending quantitative finance roots with product-focused engineering leadership. Technically hands-on, Francis contributes to notable open-source projects including linuxboot, btcd (a full Bitcoin node in Go), and tinygrad, signaling deep expertise in low-level build systems, distributed systems, and ML tooling. His work often spans integration and reliability—resolving complex build issues, extending RPC APIs, and optimizing core kernels—rather than only surface features. Based in Los Angeles and educated at MIT in Physics and Mathematics, he brings a rare combination of rigorous analytical training and pragmatic systems experience. Colleagues would describe him as entrepreneurial, detail-oriented, and adept at turning intricate technical problems into deployable, auditable solutions.
12 years of coding experience
17 years of employment as a software developer
S.B. Physics Mathematics, S.B. Physics Mathematics at Massachusetts Institute of Technology
A minimal Linux that runs as a coreboot or LinuxBoot ROM payload to provide a secure, flexible boot environment for laptops, workstations and servers.
Role in this project:
Back-end & DevOps Engineer
Contributions:2 reviews, 68 commits, 37 PRs in 2 years 10 months
Contributions summary:Francis contributed to the `linuxboot/heads` repository by addressing build issues related to the coreboot project, specifically resolving problems caused by GCC's default use of `-pie`. They also modified the build process to support Qubes Xen, updating submodule references and adjusting the Makefile to prevent unnecessary repatching during subsequent builds. Further contributions included adding support for configurable Xen versions and updating to coreboot 4.6, demonstrating a focus on build systems and integration of different components.
You like pytorch? You like micrograd? You love tinygrad! ❤️
Role in this project:
Back-end Developer
Contributions:71 reviews, 137 PRs, 183 comments in 1 year 6 months
Contributions summary:Francis primarily contributed to the core functionality of the `tinygrad/tinygrad` project, focusing on bug fixes and enhancements. Their commits addressed issues related to incorrect pad movement, and improved the loading and concatenation of different model sizes in the Llama example. They also worked on rendering NaN values and optimizing the matrix multiply-accumulate (matmul) kernels, and added a seed option to the stable diffusion example.
deep-learningpytorchmicrograd
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