Research Engineer - Reinforcement Learning, Self-Driving
Core
Conduct research on reinforcement learning (RL) and training infrastructure for large-scale self-play, VLA post-training, and closed-loop RL in neural simulation to enable end-to-end autonomous driving and robotic generalist systems.
Role type
Research Engineer (Reinforcement Learning & Autonomous Systems)
Builds
End-to-end algorithms for mass production vehicles, neural simulation tools, and research publications for top-tier conferences.
Domain
Autonomous driving, robotics, machine learning, simulation
Deliverable
production ML models | research
Required skills
Reinforcement learning (self-play, imitation, behavior learning), VLA post-training, large-scale closed-loop RL, distributed ML training infrastructure (Ray), Python, PyTorch, computer vision, robotics systems
Preferred skills
Industry experience in self-driving applications, building customer-focused software frameworks
Technologies
Ray, Python, PyTorch
Responsibilities
Develop RL training infrastructure and algorithms for autonomous driving and robotics; Collaborate with engineering teams to deploy end-to-end algorithms for mass production vehicles; Work with scientists to produce high-quality research publications.
Seniority
Individual Contributor (Open to all years of experience, potential for Tech Lead/Manager capacity)
