Senior/Staff Deep Reinforcement Learning Engineer

Responsibilities

• Formulate complex driving tasks as RL problems with well-shaped reward functions and expressive state/action representations
• Design and train model-based deep RL agents using GPU-accelerated simulation at massive scale
• Build and maintain distributed training infrastructure in JAX across large compute clusters
• Build agentic optimization systems to automatically improve code, run experiments, and iterate on RL policies
• Own the full lifecycle from problem formulation and reward design to on-vehicle inference

Requirements

• BS/MS/PhD in CS, EE, Robotics, or a related field
• Strong foundation in reinforcement learning and deep learning
• Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor)
• Hands-on experience training RL agents at scale in robotics or autonomous driving
• Proficiency in JAX or a similar functional ML framework
• Deep grasp of policy gradients, value functions, exploration-exploitation, and sim-to-real transfer
• Data-driven mindset for building experiment pipelines and analyzing training runs

Preferred Qualifications

• Publications at top venues (NeurIPS, ICML, ICLR, CoRL, RSS, ICRA)
• Experience building or working with GPU-accelerated simulators for RL training
• Track record of shipping learned components in production robotics or autonomous vehicle stacks

About the Company

DoorDash is a technology and logistics company on a mission to empower local economies. The DD Labs team builds real-time autonomous delivery systems using a pure JAX end-to-end stack.