Raphaël Bournhonesque
Machine Learning Engineer at Open Food Facts
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolRaphaël Bournhonesque is a Machine Learning Engineer based in Paris with 11 years of experience building production-ready ML systems, primarily in NLP but with solid computer vision expertise. He has delivered end-to-end solutions from research to deployment—designing image-similarity services at scale with EfficientNet and ANN, shipping transformer-based classifiers for multilingual tag detection, and improving search relevance via deployed NER models. At Open Food Facts he applies ML to real-world product data, and his open-source contributions include practical enhancements to the widely used spaCy library’s French module. Comfortable across the stack, Raphaël pairs backend engineering and mobile experience (Android) with a research-rooted education in biology and computer science, which informs his pragmatic, data-driven approach. He is particularly skilled at turning linguistic insights into robust retrieval and NLG systems that scale to millions of items.
11 years of coding experience
5 years of employment as a software developer
M.S. in Biology, Biology, M.S. in Biology, Biology at Ecole normale supérieure de Lyon
French, English, German
Github Skills (18)
kotlin10
tokenize10
debug10
fragment10
python10
multiview10
java10
javas10
tokenizer10
spacy10
android10
natural-language-processing10
nlp10
pageviews10
kotlin-android10
Programming languages (17)
Github contributions (5)
openfoodfacts/openfoodfacts-androidapp
Mar 2019 - Feb 2020
(Legacy) Native version of Open Food Facts on Android - Coders & Decoders welcome 🤳🥫
Role in this project:
Mobile Developer (Android)
Mobile Developer (Android)Contributions:19 commits, 14 PRs, 32 pushes in 11 months
Contributions summary:Raphaël primarily contributed to the native Android application for Open Food Facts. Their work focused on fixing bugs, improving the user interface, and enhancing the product summary and ingredients views. The commits reveal efforts to address specific issues, refactor code, and incorporate UI improvements, including redesigning components, and modifying UI elements for better user experience. The user demonstrates proficiency in Java/Kotlin and Android SDK, as reflected in code modifications related to various fragments and activities.
gsocfoodandroidopenfoodfactskotlin
explosion/spaCy
Jan 2017 - Nov 2017
💫 Industrial-strength Natural Language Processing (NLP) in Python
Role in this project:Back-end Developer
Back-end DeveloperContributions:22 commits, 15 PRs, 28 comments in 9 months
Contributions summary:Raphaël contributed to the spacy library, focusing on the French language module. Their commits included adding tokenizer exceptions, merging updates, and fixing typos within documentation. The user also implemented changes to the `morph_rules`, `tokenizer_exceptions`, and unit tests within the repository. They also addressed issues in the core library concerning the whitespace attribute.
fairness-mlpythondata-preprocessinglanguage-processingtokenization
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