Jorge Moya

Valencia, Valencian Community, Spain

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Summary

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Rockstar

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Jorge Moya is a versatile software engineer with 17 years of experience bridging research and production, currently at Google and working as a freelance contractor from Valencia, Spain. His background includes academic research in pattern recognition (speech and handwriting) and extensive game development experience, giving him a strong grasp of both algorithmic foundations and real-time systems. He focuses on low-level and tooling work—programming languages, code optimization, efficient algorithms, and constrained-resource environments—often tackling build systems and compiler toolchains. Jorge is an active open-source contributor to high-profile projects like LLVM and TensorFlow, where he has improved build robustness, dependency management, and debugger stability. Colleagues rely on him for pragmatic fixes that prevent subtle runtime errors (e.g., dangling pointers and subprocess error handling) and for keeping complex C++/Bazel/Bazel-like ecosystems compatible across LLVM versions. His blend of research rigor, game-engine pragmatism, and deep toolchain knowledge makes him particularly effective on projects that demand both performance and maintainability.

17 years of coding experience

9 years of employment as a software developer

Universitat Politècnica de València

English, Spanish

Stackoverflow

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Github Skills (21)

dependency-management10

debugging10

debug10

c-language10

llvm10

build-system10

lldb10

tensorflow10

compiler-construction10

system-integration10

bazel10

error-handling10

cprogramming-language10

automation9

vscode9

Programming languages (7)

C++CLLVMHTMLMLIRDartPython

Github contributions (5)

llvm/llvm-project

Feb 2020 - Apr 2025

The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.

Role in this project:

Back-end Developer

Contributions:202 reviews, 95 PRs, 130 pushes in 5 years 2 months

Contributions summary:Jorge primarily contributed to the LLVM project by addressing missing dependencies and fixing issues related to the Bazel build system for various components like MLIR and libc. Their work involved modifying BUILD files to ensure proper linking and compilation, indicating a focus on build system maintenance and dependency management. The user also reverted and re-applied patches, demonstrating an understanding of code stability and potential performance impacts. Their contributions are focused on ensuring the correct building of the LLVM compiler infrastructure.

compilerstechnologiesclangsubmittoolchain

tensorflow/runtime

Apr 2022 - Aug 2022

A performant and modular runtime for TensorFlow

Role in this project:

Back-end Developer

Contributions:17 commits in 4 months

Contributions summary:Jorge primarily focused on integrating and updating LLVM versions within the TensorFlow runtime project. Their commits involve modifying the `third_party/llvm/workspace.bzl` file to incorporate specific LLVM commit hashes and SHA256 checksums. This suggests a role in managing dependencies and ensuring the correct versions of LLVM, a critical component for performance optimization, are utilized in the runtime environment. The consistent pattern across multiple commits indicates a sustained effort in keeping the LLVM integration up-to-date.

runtimeperformantmodulartensorflow

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