Guillermo Etchebarne
Senior ML Engineer at Zapia AI
Montevideo, Montevideo, Uruguay
Summary
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Top SchoolGuillermo Etchebarne is a Senior ML Engineer with eight years of experience blending signal-processing expertise from an electrical engineering background with production-grade machine learning. He has led ML teams at Tryolabs and contributed to applied research projects at Eden before joining Zapia AI, where he currently builds end-to-end ML systems. His undergraduate thesis, DNAi, applies genome-wide approaches to complex phenotype prediction, demonstrating a rare mix of bioinformatics ambition and practical engineering. An active open-source contributor, Guillermo extended temporal feature processing and operator implementations in the high-profile TensorFlow Decision Forests project, highlighting his strengths in data manipulation and backend model infrastructure. Known for refactoring for maintainability and adding robust tests, he favors pragmatic, test-driven solutions that scale from research prototypes to production.
7 years of coding experience
5 years of employment as a software developer
Ingeniería Eléctrica, Procesamiento de señales, Ingeniería Eléctrica, Procesamiento de señales at Universidad de la República
Github Skills (7)
data-manipulation10
pandas10
tensorflow10
python10
back-end-development10
machine-learning9
api-design7
Programming languages (1)
Github contributions (5)
tensorflow/decision-forests
Jan 2023 - Jan 2023
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:8 reviews, 27 commits, 7 PRs in 17 days
Contributions summary:Guillermo primarily contributed to the development of the temporal feature processor within the TensorFlow Decision Forests repository. Their work involved extending the core functionality by adding new attribute types, refactoring code for better readability and maintainability, and implementing new operators, specifically the Assign operator, including tests. They also updated the Pandas implementation of the operators, demonstrating a focus on data manipulation and processing within the project's scope.
pythondecision-foreststate-of-the-arttrainingtensorflow
getchebarne/slai-the-spire
Aug 2023 - Mar 2025
Training a Deep Reinforcement Learning agent to beat Slay the Spire.
Contributions:45 PRs, 64 pushes, 49 branches in 1 year 8 months
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