AI/ML engineer with a double degree in Artificial Intelligence (Engineering degree at ENIB + Master's at UQAC, Canada). I design robust, reproducible, actually-deployed AI systems - from SIMD-optimized deep learning libraries in modern C++ to containerized RAG / LLM pipelines in the cloud.
📍 Brest, France · 🗣️ French (native) · English (C1) · Spanish · Mandarin (notions)
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A deep learning library built from scratch in modern C++17: compile-time tensor pipelines (variadic templates), core ops (dense, activation, loss, optimizer) and low-level SIMD vectorization to max out single-core CPU throughput.
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A complete Transformer architecture implemented from scratch in PyTorch for sequence-to-sequence translation, trained on OPUS Books with pretrained BERT / CamemBERT tokenizers. Train/inference pipeline driven by Makefile.
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A production-ready RAG system querying a vector store to return context-enriched answers, exposed through a modern REST API and fully containerized with Docker for reproducible deployment.
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From-scratch implementations of VQ-VAE, β-VAE and standard VAE, trained on MNIST for image generation & reconstruction - exploring discrete latent spaces and codebook learning.
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Languages
Deep Learning & Generative AI
MLOps & Cloud
HPC / Systems & Tools
Building AI systems from low-level C++ kernels up to cloud-deployed LLM pipelines.