Tech Stack

Description

As a Research Engineer on the Research Group, you will conduct cutting-edge research on reinforcement learning and its training infrastructure, with applications to end-to-end autonomous driving and robotic generalist. You will collaborate with leading experts to publish at top conferences and deploy algorithms into real-world autonomous systems for automotive, defense, and other industries. Your work will directly impact customers by advancing physical AI capabilities.

Requirements

• Hands-on experience in self-play RL, imitation learning, VLA post-training, or large-scale closed-loop RL in driving simulation
• Experience with large-scale RL training infrastructure (Ray preferred)
• Strong skills in Python, PyTorch, computer vision, robotics systems, and distributed ML training
• Industry experience in relevant topics (self-driving preferred)
• MSc or PhD in machine learning or computer vision with autonomy/robotics applications (nice to have)

Responsibilities

• Conduct research on large-scale self-play RL, VLA post-training, closed-loop RL with neural simulation for autonomous driving
• Work with Research Scientists and interns on high-quality publications for top-tier conferences
• Collaborate with engineering teams on ADAS, data, and simulation to deploy end-to-end algorithms for mass production vehicles
• Develop neural simulation and generation tools for autonomy development