Luis Sánchez
Web UI Developer, Architect at Globant
New Albany, Ohio, United States
Summary
🤩
Rockstar🎓
Top SchoolLuis Sánchez is a seasoned Web UI Developer and Architect with 13 years of engineering experience and nine focused on front-end design and delivery, currently leading UI teams at Globant from New Albany, Ohio. He builds responsive, testable web and hybrid mobile apps using HTML5, CSS3, modern JavaScript (React, Redux, Angular) and has driven architecture and platform rewrites for data-heavy dashboards and e-commerce storefronts. Beyond front-end leadership, he contributes to high-profile open-source ML projects—working on TensorFlow runtime, sparse tensor ops, and XLA—bringing low-level performance and numerical-computation insights unusual for a UI specialist. His background spans SharePoint customization, API integrations and mobile hybrids, making him effective at bridging product, design and performant engineering. Colleagues rely on him for clear architecture decisions, hands-on implementation, and smoothing cross-disciplinary integrations between UI and ML/compute stacks.
13 years of coding experience
8 years of employment as a software developer
Ingeniero en Sistemas Computacionales, User Interface Design, Ingeniero en Sistemas Computacionales, User Interface Design at ITESM
Spanish, English
Github Skills (19)
c-language10
lib10
integrate10
float3210
sparse-matrix10
gpu-programming10
integrations10
eigen10
tensorflow10
compiler10
floating-point10
sparse-data10
cprogramming-language10
numpy9
machine-learning9
Programming languages (10)
Github contributions (5)
openxla/xla
May 2021 - Jan 2023
A machine learning compiler for GPUs, CPUs, and ML accelerators
Role in this project:
ML Engineer
ML EngineerContributions:9 reviews, 12 commits, 17 comments in 1 year 8 months
Contributions summary:Luis made several significant contributions to the XLA compiler, primarily focusing on improving its support for numerical computation. Their work included refactoring code related to half-precision and bfloat16 data types, optimizing floating-point operations, and fixing rounding edge cases within the compiler. They also addressed platform-specific dependencies and refactored build rules for custom floating-point types, contributing to the overall efficiency and maintainability of the codebase.
compilercommunity-drivenmachine-learningmodular
tensorflow/tensorflow
May 2021 - Jan 2023
An Open Source Machine Learning Framework for Everyone
Role in this project:ML Engineer
ML EngineerContributions:707 reviews, 287 commits, 33 PRs in 1 year 8 months
Contributions summary:Luis's contributions focused on enhancing the TensorFlow library's functionality related to sparse tensors. Specifically, the user updated and extended the documentation for the `tf.sparse.transpose` operation, implementing features for matrix-vector multiplication and enabling operations such as a batch-based conversion and validation for out of bound indices, This also involved incorporating int4 support, indicating a focus on improving and optimizing core sparse tensor functionality, and adding support for int4 tensor.
pythondata-sciencedeep-learningmlmachine-learning
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