Stella Laurenzo is a seasoned engineering leader with 15+ years building high-performance ML compilers, runtimes, and production AI infrastructure, now leading AMD’s AI Group and serving as VP of Engineering at nod.ai. She combines deep compiler and backend expertise—evident from substantial contributions to the MLIR-based IREE project and TensorFlow/Lingvo quantization work—with large-scale systems experience from a long tenure at Google. Stella is skilled at bridging low-level performance engineering and developer-facing APIs, having rewritten Python bindings and optimized C++ platform support for tracing and runtime projects. Her career blends hands-on technical delivery with strategic leadership across startups and major enterprises, including MapQuest and American Express. Based in Seattle, she focuses on open-source tooling that makes hardware acceleration accessible to ML practitioners. One less obvious strength: she repeatedly modernizes build and binding layers, improving long-term maintainability as well as raw performance.
15 years of coding experience
23 years of employment as a software developer
BS Computer Engineering, BS Computer Engineering at University of Central Florida
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Role in this project:
Back-end Developer & Compiler Engineer
Contributions:1161 reviews, 652 commits, 1169 PRs in 3 years 3 months
Contributions summary:Stella primarily worked on the IREE compiler infrastructure. Their commits focused on implementing new passes for optimizing numeric precision, handling new language constructs and data types. They refactored existing features, ensuring compatibility with the latest versions of LLVM tools and the IREE project's infrastructure. In addition, they improved the Python bindings for the IREE API by re-writing function argument packing to C++ and enhancing exception and logging information.
Contributions:49 commits, 12 PRs, 16 pushes in 3 years 11 months
Contributions summary:Stella primarily focused on implementing and improving the Web Tracing Framework's C++ bindings. They integrated C++ bindings and reworked platform support to optimize the framework for both single-threaded and multi-threaded environments, including support for Myriad2 and Sparc platforms. The user also improved the code with clang-format and removed a dependency, demonstrating commitment to code quality and build system optimization.
tracingextensions
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Stella Laurenzo - Senior Director - AI Group at AMD