Hi, I’m Thomas, a French engineer currently based in the Netherlands 🇫🇷 → 🇳🇱.

I’m a Research Software Engineer with a strong background in aerospace systems engineering, now focused on building AI-driven, data-based software systems. My main interests lie at the intersection of Artificial Intelligence, complex engineering systems, and real-world applications, particularly in aerospace, mobility, and sustainability.

I started my career after studying Aerospace Engineering and Systems Engineering in Toulouse, France. I then joined ArianeGroup in Paris, where I worked for 3 years as a Systems Engineer on the Ariane 6 space launcher. Looking for broader technical challenges and international experience, I moved to the Netherlands to work at Thales, where I was responsible for deploying Model-Based Systems Engineering (MBSE) practices across engineering teams.

Driven by curiosity and a desire to go deeper into data-driven methods, I progressively transitioned toward Artificial Intelligence and Software Engineering. I completed the Machine Learning course by Stanford University (Coursera), which sparked a long-term commitment to AI. Over the past few years, I have continuously built expertise through hands-on projects and formal education, including two MicroMasters programs, one in Artificial Intelligence and one in Software Engineering (Columbia University, edX).

Today, I focus on designing and implementing robust, well-engineered AI systems, with an emphasis on:

• Python and data-centric software development
• Machine learning and optimization algorithms
• Graph-based models and complex networks
• Clean architecture, testing, and maintainability
• Bridging domain knowledge with software and AI

I’m always open to collaborating on technically ambitious projects, especially those that combine engineering rigor, AI, and real-world impact.

• Scalable Satellite Tile Inference Pipeline
  A production-oriented ML inference pipeline for satellite imagery, focusing on geospatial data handling, batch and API-based inference, model versioning, and observability. Emphasis on scalable system design and reproducibility rather than model complexity.

• PolitelySecureDevice
  A Model-Based Systems Engineering project for a smart face-recognition security device that greets known users and alerts the owner in case of intrusion.

• Connect4Game_RL
  An implementation of the Connect-4 game featuring an AI agent trained using Reinforcement Learning.

Feel free to reach me by email: thomas.le-montagner@hotmail.com or on LinkedIn: https://www.linkedin.com/in/thomas-le-montagner/