Physical AI Engineer는 차세대 자율주행을 위한 End-to-End(E2E) Planning Model을 설계·개발하고, 모델의 학습·검증을 위한 Closed-loop Simulation 환경과 파이프라인을 개발합니다.
Trajectory Generation과 Decision-making을 수행하는 E2E Planning Model부터 Closed-loop Simulation까지, 주행 상황을 바탕으로 안전한 의사결정과 trajectory를 생성하는 핵심 기술을 개발합니다. Generative AI, Imitation Learning, Reinforcement Learning, 3D 환경 재구성 및 물리 기반 Simulation 등 다양한 기술을 실제 Autonomous Driving 문제에 적용합니다.
E2E Planning Model을 직접 설계·개발하고, Closed-loop Simulation과 실차에서 성능을 검증합니다. Simulation 및 실차 주행 데이터와 실패 사례를 분석하여 모델을 개선하는 개발 사이클을 반복하며 차세대 Autonomous Driving System 개발에 기여합니다.
The Physical AI Engineer designs and develops end-to-end (E2E) planning models for next-generation autonomous driving, as well as closed-loop simulation environments and pipelines for training and validating them.
You will work with E2E planning models for trajectory generation and decision-making, closed-loop simulation, generative AI, imitation learning, reinforcement learning, 3D environment reconstruction, and physics-based simulation to solve real-world autonomous driving problems.
You will directly design and develop E2E planning models and validate their performance in closed-loop simulation and real vehicles. By analyzing simulation results, real-world driving data, and failure cases, you will continuously improve the models and contribute to next-generation autonomous driving systems.