Stage Innovation : Ingénieur Intelligence Artificielle Générative / Système de transport intelligent
Core
Develop advanced pedestrian detection and intention prediction for ADAS systems using Vision-Language Models (VLM) and temporal context graphs.
Role type
Final-year engineering student (GenAI/Computer Vision)
Builds
Production-ready ADAS perception modules and prediction algorithms
Domain
Autonomous driving / Intelligent Transportation Systems
Deliverable
production ML models
Required skills
Machine Learning, Computer Vision, Generative AI, Python, PyTorch, TensorFlow
Preferred skills
VLMs, Temporal Context Graphs, Scientific Writing
Responsibilities
Implement and evaluate comparative approaches for pedestrian detection, analyze model performance against scientific indicators, evolve software architecture, update state-of-the-art knowledge on VLMs and prediction modules, write a scientific paper
Seniority
Intern (Final-year engineering student)
