Bridging the gap between mathematical theory and production-grade code.
As a Dual Degree Engineer (ENSAI & INSEA), I don’t just train models; I build scalable AI products. My approach is “Full Stack”: from raw data extraction to MLOps deployment on GCP.
Currently Data Scientist & ML Engineer @Opsci, focusing on Computer Vision and LLM integration.
Creator of “AI Papers Explained”: Founder of a technical podcast turning complex Arxiv papers (Mamba, RAG, Transformers) into accessible audio breakdowns using GenAI workflows. Distributed on Spotify & YouTube.
Core Stack:

• GenAI & NLP: LLMs (OpenAI, Ollama), RAG, Embeddings, Transformers.
• Computer Vision: YOLO, CLIP, DINO, Roboflow.
• Engineering: Python, SQL, GCP (Cloud Run, Task, Functions), Git.
• Maths: Strong statistical foundation (Ensai/Insea DNA).

Philosophy: I believe talent is nothing without opportunity and grit. I bring that dedication to solving complex industrial problems, whether it’s optimizing latency or cutting annotation costs by 65%.

Open to discussing Tech, GenAI, or the future of MLOps.