Working student thesis project focused on developing efficient on-device ML models for AR glasses, specifically exploring event-based sensing and processing combined with deep learning techniques to meet strict latency, energy, and bandwidth constraints on embedded hardware. The role involves designing, prototyping, and evaluating models, exploring efficiency techniques, and demonstrating proof-of-concepts on AR hardware.