Description
The role designs and implements decision-planning algorithms for autonomous lane changes in mapless and SD-map scenarios, focusing on gap-finding, robust decision-making, and system-level KPIs. It involves integrating algorithms into an autonomous driving architecture, solving noisy-input and unstable-prediction challenges, optimizing algorithms through research, and tracking project milestones for mass production. The position requires a master's degree or higher in a relevant field, expertise in artificial intelligence and autonomous driving, strong C++ and embedded-systems knowledge, and proficiency in C++ and Python.
