Morgan Funtowicz
Machine Learning Engineer at Hugging Face
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolMorgan Funtowicz is a Machine Learning Engineer with 11 years of experience, currently leading ML optimizations at Hugging Face from Paris where he focuses on scaling deep learning for machine reading, control, and planning in distributed environments. He blends research and production experience—from Microsoft Research and NAVER Labs to Hugging Face—delivering optimized inference and training pipelines (notably contributions to Transformers, Tokenizers, and the Optimum library). His work spans model quantization, ONNX/Intel LPOT integrations, TensorRT backends, and CI/CD for large language model inference, reflecting a rare full-stack ML ops + systems skillset. Morgan also has a history of contributing to core deep learning frameworks (CNTK, PyTorch) and building distributed HPO engines, showing a practical focus on squeezing performance from both models and infrastructure.
11 years of coding experience
3 years of employment as a software developer
DUT, Informatique, Acquis, DUT, Informatique, Acquis at IUT de DijonEngineer's degree, Ingénierie informatique, Engineer's degree, Ingénierie informatique at Polytech'Lyon
English, German
Stackoverflow
85reputation
2kreached
2answers
2questions
Github Skills (42)
transformers10
tokenize10
pytorch10
docker10
python10
machine-learning10
onnx10
dockers10
cicd10
tokenizer10
tensorflow10
onnxruntime10
natural-language-processing10
pipeline10
quantization10
Programming languages (10)
Github contributions (5)
huggingface/text-generation-inference
Nov 2023 - Mar 2025
Large Language Model Text Generation Inference
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:28 reviews, 24 PRs, 302 pushes in 1 year 4 months
Contributions summary:Morgan primarily contributes to the back-end infrastructure of the text generation inference system. The commits demonstrate the implementation of new backend features and the improvement of existing ones, specifically related to the TensorRT-LLM backend. The user also actively participates in the DevOps aspects of the project, including configuring CI/CD pipelines, Docker builds, and build system configuration.
nlppytorchlanguage-modelbloombert
huggingface/optimum
Aug 2021 - Dec 2022
🚀 Accelerate inference and training of 🤗 Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools
Role in this project:ML Engineer
ML EngineerContributions:35 reviews, 17 commits, 21 PRs in 1 year 4 months
Contributions summary:Morgan's commits primarily focused on modifications and enhancements related to the `optimum` library, which provides tools for accelerating the inference and training of Transformer models. Their contributions include renaming the library, adding and modifying configuration parameters for quantization, updating dependencies, and making improvements to quantization functionalities. The user's work involved interaction with ONNX Runtime and Intel's LPOT (Low Precision Optimization Tool) for model optimization and quantization.
trainingoptimization-toolstransformersintelhardware
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