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Xavier FagetXF

Xavier Faget

Geospatial AI Engineer | Algorithm & Software Dev

600 €/jour
Anglet, FR
8-15 ans

Délai de réponse moyen : 1h

À propos de Xavier

I’m a Geospatial AI Engineer with a theoretical physics background, specializing in deep learning for GIS and radar applications. Since March 2020, I’ve been working as an independent researcher while continuing to collaborate with ONERA, building and training neural networks for real-world geospatial and radar pipelines.

I cover the full workflow end to end: designing and generating training data, curating datasets, training and tuning models (classification, object detection, image segmentation), and developing post-processing steps to improve overall system performance and robustness. I’m equally comfortable with research and software delivery, with C++ and scientific computing experience.

In the past, I also co-founded Supercube Studio as CTO, where I led technical execution and shipped an independent game available on Steam, which reflects my ability to turn complex ideas into reliable, shipped software.

I’m open to a wide range of technical freelance challenges. Curious by nature, and backed by a broad, cross-disciplinary skill set, I can ramp up quickly and become productive fast, even when the topic doesn’t perfectly match my current stack.
  • Français

    Bilingue ou natif

  • Anglais

    Capacité professionnelle complète

  • Espagnol

    Capacité professionnelle limitée

En télétravail uniquement
Travaille majoritairement à distance

Expériences

  • Freelance
    Geospatial AI Engineer | Algorithm & Software Developer
    DÉFENSE & ARMÉE
    mars 2020 - Aujourd'hui (6 ans et 3 mois)
    Anglet, France
    Since March 2020, I have worked as an independent researcher, continuing to collaborate with my former team at ONERA. In this role, I focus on Geographical Information Systems (GIS) and applied deep learning, developing and training models for radar and geospatial applications—including classification, object detection, and image segmentation. I handle the full pipeline: building and curating training datasets, training and tuning models, and designing post-processing to improve end-to-end performance.
    Deep Learning Image classification Image segmentation Computer Vision Geographic Information Systems (GIS)
  • ONERA
    Research engineer
    DÉFENSE & ARMÉE
    juillet 2018 - mars 2020 (1 an et 8 mois)
    Palaiseau, France
    I contributed to several radar-related projects, including the development of a custom C++ simulation engine, the design of procedural generation methods for realistic urban environments, and the creation of high-quality datasets for deep learning workflows
  • CEA
    PhD
    DÉFENSE & ARMÉE
    janvier 2015 - janvier 2018 (3 ans)
    Monts, France
    I was involved in the developpment of a 2D free-space measurement system,
    whose propose is the non-destructive characterization of manufactured
    magneto-dielectric structures. This includes data processing, physical
    modelling of a multistatic bench and treatment of the inverse problem.
    Modélisation physique Algorithmes Problem Solving

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Formations

  • PhD
    Aix-Marseille Université | CEA le Ripault
    2018
    I was involved in the developpment of a 2D free-space measurement system, whose propose is the non-destructive characterization of manufactured magneto-dielectric structures. This includes data processing, physical modelling of a multistatic bench and treatment of the inverse problem.
  • Master's degree, Theoretical and Mathematical Physics
    Université François Rabelais de Tours
    2014
    The first year of this two year master's course relied on the work of the previous years and went further studying physical mathematics, physics of continuous matter, quantum and statistical physics, atomic and subatomic physics, classical field theory, magnetism and numerical simulations. The second year focuses on non-linear phenomena like solitons, quantum field theory, general relativity, dynamical systems and chaos and numerical simulations as well.

Compétences

Catégories