David Majnemer
Principal Engineer at Google
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolDavid Majnemer is a Principal Engineer based in San Francisco with 17 years of systems, compiler, and ML compiler experience driving performance-sensitive infrastructure at Google. He leads xPU ML compiler efforts, with a track record from kernel and LLVM/Clang work to owning XLA/TPU matrix multiply and convolution performance. A prolific open-source contributor, he has submitted correctness and performance fixes to high-profile projects such as LLVM, Clang, TensorFlow, JAX, and Abseil—often addressing tricky numerical stability and backend codegen issues (including NVPTX bf16 support). Colleagues rely on him for deep compiler internals, cross-platform robustness, and squeezing deterministic precision out of accelerator runtimes. His background includes low-level systems work at Apple on storage and Linux scheduler optimizations at Google, which informs a pragmatic approach to compiler and runtime engineering. He combines rigorous testing and bug-hunting with a habit of surfacing subtle numerical edge cases that improve reliability across CPUs, TPUs, and GPUs.
17 years of coding experience
11 years of employment as a software developer
Bachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at University of Illinois Urbana-Champaign
Github Skills (62)
simplify10
c-language10
probabilistic-programming10
float3210
numerical10
computation10
python10
template-metaprogramming10
multithreading10
llvm10
testing10
machine-learning10
internals10
lldb10
standard-library10
Programming languages (12)
Github contributions (5)
openxla/xla
Jan 2017 - Jan 2023
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 reviews, 279 commits, 7 comments in 6 years 1 month
Contributions summary:David contributed tests and code changes to the XLA project, a machine learning compiler. Their work focused on adding tests for specific computations involving floating-point operations, such as the square root and handling of NaNs. The user also made changes to the algebraic simplifier to optimize code, including power-of-two division and reassociation patterns.
compilercommunity-drivenmachine-learningmodular
llvm-mirror/clang
Jun 2011 - Jul 2017
Mirror kept for legacy. Moved to https://github.com/llvm/llvm-project
Role in this project:Back-end Developer
Back-end DeveloperContributions:894 commits in 6 years 2 months
Contributions summary:David made several changes related to the Clang compiler, specifically focusing on code adjustments, including fixing edge cases when handling variable-length arrays and addressing issues with exception specifications. They implemented support for MSVC-style features like __declspec(noalias), and made code improvements related to memory management. Additionally, the user contributed to the correct handling of template arguments, particularly for class and member function pointers, indicating a strong understanding of compiler internals.
keptwindowsllvmcc-plus-plus
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