Guillaume Genthial

Paris, Ile-de-France

Join Prog.AI to see contacts

Summary

🤩

Rockstar

🎓

Top School

Guillaume 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.

10 years of coding experience

7 years of employment as a software developer

CPGE, Maths - Physique - Informatique, CPGE, Maths - Physique - Informatique at Lycée Sainte Geneviève

Master of Science (M.Sc.), Applied Mathematics, Master of Science (M.Sc.), Applied Mathematics at École Polytechnique

Licence 3, Philosophie, Licence 3, Philosophie at University of Paris I: Panthéon-Sorbonne

Master 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

build-automation9

crf9

nlp9

seq2seq8

json8

Programming languages (4)

TypeScriptC++CSSPython

Github contributions (5)

guillaumegenthial/sequence_tagging

Mar 2017 - Sep 2018

Named Entity Recognition (LSTM + CRF) - Tensorflow

Role in this project:

ML Engineer

Contributions:26 commits, 6 PRs, 23 pushes in 1 year 6 months

Contributions summary:Guillaume implemented core functionalities for a Named Entity Recognition (NER) model using an LSTM-CRF architecture in TensorFlow. Their contributions included adding character-level LSTM embeddings to the model to enhance performance and improving the overall structure by incorporating docstrings. The user also introduced various features, showcasing the refinement and expansion of the NER model.

nlpnamed-entity-recognitionentity-recognitionentitylstm

cs230-stanford/cs230-code-examples

Jan 2018 - Feb 2018

Code examples in pyTorch and Tensorflow for CS230

Role in this project:

ML Engineer

Contributions: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.

pytorchdeep-learningcomputer-visiontensorflownatural-language-processing

Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.

Request Free Trial