Senior/Staff Deep Reinforcement Learning Engineer

What you'll do

• Formulate complex driving tasks as RL problems with well-shaped reward functions.
• Design and train model-based deep RL agents using GPU-accelerated simulation at scale.
• Build and maintain distributed training infrastructure in JAX across large compute clusters.
• Develop agentic optimization systems for automatic improvement of RL policies.
• Ensure seamless integration of learned components with the autonomy stack.

What we're looking for

• BS/MS/PhD in CS, EE, Robotics, or related field with strong reinforcement learning and deep learning foundation.
• Hands-on experience training RL agents at scale in robotics, autonomous driving, or real-time decision-making domains.
• Proficiency in JAX or similar functional ML framework; comfort with JIT compilation, vectorized environments, GPU-accelerated simulation.
• Deep understanding of core RL concepts including policy gradients, value functions, exploration-exploitation strategies.
• Ability to formulate complex tasks as RL problems and design well-shaped reward functions for expressive state/action representations.