Quentin Lhoest
Open Source & Machine Learning Engineer at Hugging Face
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolQuentin Lhoest is an Open Source and Machine Learning Engineer at Hugging Face with seven years of experience building production-ready ML tooling and datasets. He maintains core components of the Hugging Face ecosystem—contributions include integrating DPR into Transformers, enhancing the Datasets library (CSV loader features and JAX support), and improving the Hub client and evaluation tooling used widely by the community. Quentin blends backend engineering and ML research skills to ship robust data pipelines, metric implementations, and model retrieval features that power retrieval-augmented generation and large-scale evaluation. Based in Paris, he has a strong academic foundation from CentraleSupélec, ENS Paris-Saclay and EPFL and a track record of moving research into usable engineering. An often-overlooked strength is his attention to developer experience and offline-first tooling (HF_HUB_OFFLINE), which helps the ecosystem scale to diverse environments. He’s passionate about democratizing high-quality ML through open source and reproducible datasets.
7 years of coding experience
3 years of employment as a software developer
Intensive preparatory courses- Mathematics, Physics, Intensive preparatory courses- Mathematics, Physics at Lycée Faidherbe, LilleMaster of Engineering - MEng, Applied maths, Computer Science, Master of Engineering - MEng, Applied maths, Computer Science at CentraleSupélecM2 in Mathematics, Vision, Learning (MVA), Artificial Intelligence, M2 in Mathematics, Vision, Learning (MVA), Artificial Intelligence at École normale supérieure Paris-SaclayMaster's semester (exchange student), Computer Science, Data Science, Master's semester (exchange student), Computer Science, Data Science at Ecole polytechnique fédérale de Lausanne
French, English, Spanish
Stackoverflow
156reputation
29kreached
9answers
0questions
Github Skills (40)
tokenize10
caching10
pytorch10
hub10
pyarrow10
python10
evaluation10
load-data10
pre-trained-model10
model-driven10
data-set10
testing10
machine-learning10
datasets10
model-building10
Programming languages (10)
Github contributions (5)
huggingface/datasets
Apr 2020 - Jan 2023
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
Role in this project:
Backend Developer & ML Engineer
Backend Developer & ML EngineerContributions:66 releases, 4813 reviews, 1056 commits in 2 years 9 months
Contributions summary:Quentin was responsible for implementing a new feature for the CSV loader, which included adding a "features" parameter to the CSV class to allow users to specify column types in CSV files. They took into account the "features" parameter when building the cache directory, added tests, and fixed a minor typo in the text dataset. Additionally, the user implemented and tested a major improvement with the incorporation of JAX features for optimized data processing.
ml-modelstensorflownatural-language-processingmanipulationdata-science
huggingface/evaluate
Apr 2020 - Mar 2022
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
Role in this project:ML Engineer
ML EngineerContributions:3 releases, 86 reviews, 196 commits in 1 year 11 months
Contributions summary:Quentin made several contributions related to the evaluation of machine learning models. Their commits focused on adding and fixing metrics for model evaluation, especially for the SQuAD and XNLI datasets. They also updated dependencies, including those for TensorFlow, and released multiple versions of the library, improving the evaluation process.
evaluateevaluation-frameworkdata-scienceevaluationmachine-learning
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