Senior Deep Reinforcement Learning Engineer, Autonomous Driving

What you'll do

• Build and implement new Reinforcement Learning algorithms for autonomous vehicle decision-making and planning.
• Develop and maintain scalable training pipelines and simulation environments for RL training.
• Integrate RL models into the unified autonomous driving stack with perception and planning teams.
• Benchmark RL model performance against imitation learning baselines in complex urban environments.
• Optimize and deploy RL models to production-grade automotive hardware.
• Implement and debug complex RL systems using PyTorch, TensorFlow, C++, and Python.

What we're looking for

• BS or higher in Computer Science, Robotics, Electrical Engineering, or a related field (or equivalent experience).
• 12+ years of experience in the related field.
• Solid background in Reinforcement Learning, including policy gradient methods, actor-critic architectures, and on-policy and off-policy RL.
• Proficiency in PyTorch or TensorFlow with real experience in RL-related algorithms.
• Experience in C++ and Python development for real-time systems.
• Strong analytical and problem-solving skills with a track record of implementing and debugging complex RL systems.
• Background in shipping autonomous driving features or embodied AI (preferred).
• Experience with generative models, large-scale data flywheels, or training policies on own rollout distributions (preferred).