Guillaume Genthial
Agent Engineer at Sierra
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolGuillaume Genthial is an experienced machine learning engineer and AI leader with a decade of hands-on experience building production NLP and ML systems, from clinical-text information extraction to recommendation and KYC fraud detection. He co-founded and served as CTO of Fragment (YC S23), led ML teams at MetaMap and Criteo AI Lab, and earlier contributed research-quality work at Stanford on data augmentation for grammar correction. Comfortable across research, engineering and DevOps, he has implemented LSTM-CRF NER models, seq2seq image-to-LaTeX pipelines, and scalable model training tooling in PyTorch/TensorFlow—work reflected in active open-source contributions including CS230 code examples and several model repos. Based in Paris, he pairs rigorous academic training from École Polytechnique and Stanford with a pragmatic focus on deployment, automation, and A/B testing. An interesting aside: he blends technical depth with philosophical studies (Licence in Philosophy), which informs his careful, systems-level approach to ML product decisions.
11 years of coding experience
7 years of employment as a software developer
CPGE Maths - Physique - Informatique, CPGE Maths - Physique - Informatique at Lycée Sainte GenevièveMaster of Science (M.Sc.) Applied Mathematics, Master of Science (M.Sc.) Applied Mathematics at École PolytechniqueLicence 3 Philosophie, Licence 3 Philosophie at University of Paris I: Panthéon-SorbonneMaster of Science (M.Sc.) Computational and Mathematical Engineering, Master of Science (M.Sc.) Computational and Mathematical Engineering at Stanford University
French, English, German, Spanish
Github Skills (18)
named-entity-extraction10
pytorch10
named-entity-recognition10
entity-extraction10
python10
machine-learning10
lstm10
tensorflow10
data-processing10
hyperparameter-tuning10
natural-language-processing9
build-automation9
crf9
nlp9
seq2seq8
Programming languages (5)
Github contributions (5)
cs230-stanford/cs230-code-examples
Jan 2018 - Feb 2018
Code examples in pyTorch and Tensorflow for CS230
Role in this project:
ML Engineer
ML EngineerContributions:40 commits, 2 PRs, 36 pushes in 21 days
Contributions summary:Guillaume implemented and refined components related to machine learning model training and hyperparameter tuning within a PyTorch and TensorFlow code example repository. They added logging and JSON dump functionality to the utility files, enhancing the model's operational capabilities. Further contributions included the addition of a hyperparameter search feature, allowing for systematic experimentation with different learning rates. The user also made subsequent code cleanup and naming improvements.
pytorchtensorflowcomputer-visionnatural-language-processing
guillaumegenthial/im2latex
Sep 2017 - Dec 2017
Image to LaTeX (Seq2seq + Attention with Beam Search) - Tensorflow
Role in this project:Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:42 commits, 15 pushes, 1 branch in 2 months
Contributions summary:Guillaume primarily worked on the `data_generator.py` and related files, which suggests they were developing and modifying data processing components. They also contributed to `decoder.py` indicating involvement in the core model implementation. The commits also feature modifications to the build pipeline and associated configurations, suggesting responsibilities in DevOps and build automation.
beam-searchlatexseq2seqtensorflowseq2seq-attn
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