Abdeljalil Jliouat

ML Engineer

Machine Learning Engineer specializing in neural architecture search, multi-modal learning, and efficient training methods for Large Language Models (LLMs) and Computer Vision models.

Tech Stack

Academic Background

Engineering Degree in Data Science (2012-2014)
Focus: Efficient architectures for multi-modal learning

Engineering Degree in Computer Science and Applied Mathematics (2007-2012)
Focus: Full-stack development and mathematical modeling

Work Experience

• Lead ML Engineer, MX4 AI, Tech Startup, Paris & Rabat (2024-Present)

  At MX4 AI, I lead the development of optimized LLM-based conversational assistants and computer vision systems for industrial applications. My work focuses on implementing efficient fine-tuning techniques and building robust MLOps pipelines to ensure production-ready AI solutions.

• Lead AI Engineer, Serve the City, NGO, Paris (2023-Present)

  As the Lead AI Engineer at Serve the City, I design and implement advanced AI solutions to improve volunteer engagement and project management. My work focuses on creating scalable systems that drive impact through state-of-the-art LLMs and information retrieval techniques.

• Lead Data Scientist, Merci Jack, Tech Startup, Paris (2020-2023)

  At Merci Jack, I led the development of multimodal deep learning models and optimized inference pipelines for deployment on edge devices. My role involved integrating cutting-edge technologies to deliver high-performance solutions in a resource-constrained environment.

• Lead Data Scientist, Société Générale, Retail Banking, Paris (2014-2020)

  In my role at Société Générale, I spearheaded the development and deployment of AI-driven solutions to address critical business challenges such as churn prediction, fraud detection, and workflow automation. I worked closely with stakeholders to ensure our solutions delivered measurable business value.

Contact

For collaborations: contact@ajliouat.com