Marc Sun
Machine Learning Engineer at Hugging Face
Paris, Ile-de-France
Summary
🤩
Rockstar🎓
Top SchoolMarc Sun is a machine learning engineer based in Paris with six years of experience building and deploying production-ready ML systems and open-source tooling. Currently on the Hugging Face open-source team, he has contributed to flagship projects like diffusers, accelerate, and transformers—improving model loading/sharding, quantized 4/8-bit support, MPS compatibility, and serialization for large-model inference. His background spans applied data science roles where he designed patented AI algorithms, doubled Transformer inference speed with ONNX, and delivered substantial recommendation and retrieval improvements that increased conversion and precision metrics. Marc combines strong mathematical training from CentraleSupélec and Columbia with hands-on engineering, shipping practical fixes that bridge research models and scalable deployment. He’s comfortable across the ML stack—from low-level device mapping and checkpoint formats to end-to-end pipelines—and has a knack for performance-focused, reproducible engineering that isn’t always visible in academic papers.
6 years of coding experience
3 years of employment as a software developer
BSc in Engineering, MSc in Applied Mathematics, BSc in Engineering, MSc in Applied Mathematics at CentraleSupélecMaster of Science - MS, Management Science and Engineering, Master of Science - MS, Management Science and Engineering at Columbia Business SchoolMaster of Science - MS, Management Science and Engineering, Master of Science - MS, Management Science and Engineering at Columbia University in the City of New YorkHigher School Preparatory Classes, Mathematics, Physics and Chemistry, Higher School Preparatory Classes, Mathematics, Physics and Chemistry at Lycée Louis-le-Grand
English, French, Chinese
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (23)
transformers10
pytorch10
quants10
acc10
python10
acceleration10
machine-learning10
stable-diffusion10
accelerator10
mlops10
deep-learning10
quantization10
nlp10
metal-performance-shaders9
serializer9
Programming languages (3)
Github contributions (5)
huggingface/accelerate
May 2023 - Apr 2025
🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support
Role in this project:
ML Engineer
ML EngineerContributions:1 release, 478 reviews, 207 PRs in 1 year 10 months
Contributions summary:Marc primarily contributed to the `accelerate` repository by fixing issues related to PyTorch model quantization, specifically addressing bugs in 4-bit and 8-bit model loading and dispatching. Their work included adding support for MPS (Metal Performance Shaders) on macOS, which involved modifying big model inference, adding new tests, and improving overall model performance. They also implemented a `save_model` function for model serialization and integrated Peft (Parameter-Efficient Fine-Tuning) compatibility, showcasing their focus on practical deployment and usability enhancements.
pytorchpytorch-modelsmixed-precisiondeep-learninggpu
huggingface/transformers
May 2023 - Apr 2025
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Role in this project:ML Engineer
ML EngineerContributions:1044 reviews, 291 PRs, 427 pushes in 1 year 10 months
Contributions summary:Marc primarily contributed to the core functionality of the `huggingface/transformers` repository. Their work involved modifying the behavior of device mapping when loading and training models. The commits show a focus on quantization aspects, specifically, improving support for 4-bit and 8-bit models, incorporating new GPTQ integration, and updating the code related to the torchao optimizer. They have also made corrections and improvements to the underlying code for enhanced system performance.
pythonbertspeech-recognitionstate-of-the-artflax
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