Mathieu Martial
Paris, Ile-de-France
Summary
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Rockstar🎓
Top SchoolMathieu Martial is an ML Research Engineer based in Paris with two years of hands-on experience building practical LLM and ML solutions. At Giskard he co-developed end-to-end RAG pipelines, improved retrieval and F1 scores through targeted fine-tuning, and contributed fairness mitigation code to an open-source QA platform—work he documented in technical articles including a Hugging Face piece. He’s comfortable turning research into product-ready components, from multimodal summarization pipelines to lightweight fine-tuning strategies that prioritize data efficiency. Trained in AI and computer engineering at Polytechnique Montréal and Télécom SudParis, Mathieu combines a strong mathematical background with creative problem-solving (previously applied to 3D modeling for film). He’s now seeking a junior role as an LLM Engineer, ML Engineer, or Data Scientist where he can scale his RAG, evaluation, and model-safety expertise.
2 years of coding experience
2 years of employment as a software developer
High School Diploma, Baccalauréat Scientifique, High School Diploma, Baccalauréat Scientifique at Lycée LavoisierMPSI/MP*, Mathematics, MPSI/MP*, Mathematics at Lycée FénelonArtificial Intelligence, Artificial Intelligence at Polytechnique MontréalEngineer's degree, Computer Engineering, Engineer's degree, Computer Engineering at Télécom SudParis
French, English, Spanish, Japanese
Github Skills (13)
quality-assurance10
ai-security10
cicd9
continuous-integration9
llmops9
llm9
testing9
reinforcement-learning9
artificial-intelligence9
evaluation-framework9
mlops9
machine-learning8
ai8
Programming languages (1)
Github contributions (4)
Sakayatsp/Automatic-animation-generation-with-lip-syncing
Nov 2023 - Nov 2023
Contributions:4 pushes, 1 branch in 1 day
Giskard-AI/giskard
Jan 2024 - May 2024
🐢 Open-Source Evaluation & Testing for AI & LLM systems
Contributions:4 reviews, 1 PR, 11 pushes in 4 months
continuous-integrationtesting-toolsquality-assuranceml-validationmlops
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