Tasks:
- * Build closed-loop VLA/WAM training and evaluation frameworks
- * Build simulation scenarios from road-test data
- * Develop simulation runtime monitoring and fault handling
- * Generate generalized and long-tail scenarios
- * Improve simulation determinism and reproducibility
Perks/Benefits:
Skills/Tech stack required:
[Autonomous Driving] [Autonomous driving perception] [Autonomous driving perception, localization, and planning] [C#] [C++] [Concurrent Systems] [CUDA] [Cyber RT] [Data Structures] [Data Structures and Algorithms] [DDS] [Deterministic simulation] [Distributed simulation] [Docker] [GPU Inference] [GPU inference optimization] [Inference Optimization] [Kubernetes] [Learning frameworks] [Linux] [LogSim] [Multithreading] [Python] [PyTorch] [Reinforcement Learning] [Reinforcement Learning Frameworks] [ROS]
Educational requirements:
[Master's Degree]
Role(s):
[Autonomous Driving Simulation Engineer] [Engineer] [Simulation Engineer]