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Jules DecaesteckerJD

Jules Decaestecker

AI Engineer | GenAI Specialist (LLM & RAG), Vision

€550/day
Paris, FR
3-7 years

Average response time: 1 hour

Freelancer profile translated to English.
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About Jules

Graduated from the MVA Master (ENS Paris-Saclay) and IMT Atlantique, I assist companies in the design and deployment of cutting-edge Artificial Intelligence solutions.
My expertise is divided into three major pillars:

🚀 Generative AI & LLM:
Design of complex agentic systems and RAG (Retrieval-Augmented Generation) pipelines. I automate critical business processes (banking, insurance) by ensuring data reliability and governance (Human-in-the-loop). Expertise in Fine-tuning (LoRA, PEFT) and inference optimization.

👁️ Computer Vision & Research:
Specialist in emerging architectures (Mamba, Transformers) for segmentation and classification. Author of scientific publications (CVPR, EUSIPCO), I transform the state-of-the-art into high-performance industrial solutions, particularly for embedded systems (NVIDIA Orin).

⚙️ Engineering & Scale:
Mastery of distributed training (FSDP, Tensor Parallelism) and deployment (API, Docker, Monitoring). I don't just create models; I build robust infrastructures capable of supporting models with billions of parameters.

Why work with me?
Dual Culture: Academic rigor (MVA) and engineering pragmatism (IMT).
Product Vision: Former entrepreneur, I understand your business challenges and the ROI of your AI projects.
Modern Stack: PyTorch, LangChain, FastAPI, Docker, CUDA.
Available for strategic expertise, R&D, or AI product acceleration missions.
  • French

    Native or bilingual

  • English

    Fluent

Remote only
Primarily works remotely

Experience

  • Thales
    AI Research Intern
    April 2025 - September 2025 (5 months)
    • Implementation of Mamba models for semantic segmentation.
    • TensorRT optimization for inference on embedded systems (NVIDIA Orin).
    • Comparative study SOTA vs Transformers (ViT).
    Deep Learning Computer Vision Pytorch Python
  • Polynom
    Data Scientist LLM
    April 2024 - September 2024 (5 months)
    • Fine-tuning of LLMs (Hugging Face, LoRA) and optimization of RAG pipelines (Retriever-Ranker).
    • End-to-end evaluation of model performance in production.
    Docker Python Machine learning LLM RAG

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