Gautier Dagan is a PhD-level NLP researcher and machine learning engineer with 11 years of experience building production-ready AI systems and startups across Europe and the UK. Currently a Member of Technical Staff at Cohere, he combines deep research (PhD candidate at University of Edinburgh, Meta AI Code Generation internship) with hands-on engineering—implementing transformer-based augmentation models in prominent open-source projects like NL-Augmenter. He has a track record of architecting serverless data pipelines and OCR solutions at scale, cofounding a SaaS sold to 70+ enterprise clients, and advising deep-tech investments for university spin-outs. Comfortable bridging academia and product, Gautier repeatedly moves models from simulation and research into robust, deployable systems. An uncommon strength is his fluency across the full ML lifecycle—from multi-agent language evolution experiments to production infra and deployment optimizations.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Natural Language Processing, Doctor of Philosophy - PhD Natural Language Processing at The University of Edinburgh
High School IB Diploma, High School IB Diploma at United World College Mostar
Master's degree Artificial Intelligence, Master's degree Artificial Intelligence at University of Amsterdam
Bachelor's degree Computer Science Economics and International Studies, Bachelor's degree Computer Science Economics and International Studies at Northwestern University
NL-Augmenter 🦎 → 🐍 A Collaborative Repository of Natural Language Transformations
Role in this project:
ML Engineer
Contributions:3 reviews, 9 commits, 1 PR in 2 months
Contributions summary:Gautier implemented and refined a transformer-based natural language augmentation model. Their work involved creating a `TransformerReplace` class for token replacement, using a pre-trained transformer and spaCy. Subsequent commits focused on optimizing the augmentation process, including using random sampling to ensure the desired number of words are changed, and adding a truncation feature. They also refactored the code, updating documentation and fixing typing issues.
Contributions:50 commits, 49 pushes, 1 branch in 25 days
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Gautier Dagan - Member Of Technical Staff at Cohere