CV

Education

• M.S. in ML and Data Science, EPITA, 2024
• B.S. in Software Engineering, EPITA, 2022

Work experience

• Spring 2024 - Present: ML/MLOps Engineer @ Valeo Brain Division
  • Co-developed L2+/L3 autonomous driving features (lane detection, vehicle detection, and multi-object tracking) using SOTA research for pseudo-label generation comparable to manual annotation
  • Led the development of scalable Dataflow LiDAR perception pipelines enabling 100× faster throughput than manual annotation with only a slight KPI reduction.
  • Implemented a training pipeline with KFP and Pytorch Lightning for on-board semantic segmentation.
  • Developed internal cloud-based platform for point-cloud visualization, dataset creation and pipeline triggering, reducing data-access time from hours to ~seconds and eliminating egress-heavy workflows.

Personal projects

• LeRobot Hackathon / LeKiwi
  • Won the 2025 GOSIM AI LeRobot x Seeed studio hackathon in Paris
  • Built a mobile base for my SO-100 (LeKiwi)
  • Developed face tracking and voice localization with dora-rs and ODAS
• Deep Learning for Perception
  • Trained multiple Deep Learning models from scratch on ImageNet with PyTorch Lightning
  • Reached original ResNet paper’s performance (92% Acc@5) on a 20e budget

Skills

• Programming languages: Python (3+ years), C/C++ (2 years)
• Google Cloud Platform (Dataflow, KFP)
• ML framework: Pytorch (2+ years)
  • Pytorch Lightning
  • Weights and biases
• Hands on experience with model training for computer vision tasks (image classification, semantic segmentation)