Eric Gaudet
Senior Machine Learning Engineer at Bonfy.AI
San Jose, California, United States
Summary
🤩
Rockstar🎓
Top SchoolEric Gaudet is a Senior Machine Learning Engineer with 13+ years building scalable systems and production ML at companies from Facebook to Moveworks and most recently Bonfy.AI. He blends low-level coding fluency in Java, Python, C and Bash with large-scale data tooling (Hadoop, Pig, MySQL) to deliver reliable text classification, information extraction and visual search pipelines. At Facebook he shipped production-grade infrastructure and on GitHub contributed substantive improvements to the widely used PyText framework, adding configurability, defaults, metrics and refactors that improve modularity and testing. Comfortable managing clusters and mentoring teams, he pairs a disciplined, clean coding style with excellent debugging skills and a knack for working in diverse codebases. Based in San Jose, he favors hands-on work on challenging problems and brings an engineer-first ethic and integrity to both product and platform efforts. An early career that includes teaching math and founding a computer lab hints at his long-standing commitment to mentorship and practical education.
13 years of coding experience
24 years of employment as a software developer
Master's degree Physics, Master's degree Physics at Nantes UniversitéLycee francois truffault
English, Spanish, French
Github Skills (11)
unit-testing10
configuration-management10
pytorch10
machine-learning10
nlp10
python10
natural-language-processing10
json9
web-framework9
github8
tensorflow4
Programming languages (13)
Github contributions (5)
facebookresearch/pytext
Dec 2018 - Sep 2019
A natural language modeling framework based on PyTorch
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:3 releases, 87 commits, 142 PRs in 9 months
Contributions summary:Eric primarily focused on enhancing the PyText framework. They implemented a testing framework to ensure the configurability of JSON files, adding and testing new features. Furthermore, the user added default configurations for different tasks, such as the LMTask, and exposed metric channels. They also contributed to refactoring and code cleanup, by renaming a word to token tensorizer, enhancing modularity, and improving performance.
pytorchnlpbertmachine-learningnatural-language
Titousensei/bluesaga
Aug 2016 - Sep 2016
Contributions:16 releases, 3 commits, 136 pushes in 1 month
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