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)