Senior/Staff Deep Reinforcement Learning Engineer

DoorDash USA • San Francisco, CA

1d

About The Position

As a Senior/Staff Deep RL Engineer, you will design, train, and deploy deep reinforcement learning policies that make real-time driving decisions for our autonomous vehicles. You will own the full lifecycle, from problem formulation and reward design through large-scale distributed training to on-vehicle inference. You'll help define how learned components compose with the rest of the autonomy stack to produce robust, shippable behavior.

Requirements

• BS/MS/PhD in CS, EE, Robotics, or a related field, with a strong foundation in reinforcement learning and deep learning.
• Hands-on experience training RL agents at scale, ideally in robotics, autonomous driving, or other real-time decision-making domains.
• Proficiency in JAX or a similar functional ML framework; comfort with JIT compilation, vectorized environments, and GPU-accelerated simulation.
• Deep grasp of core RL concepts: policy gradients, value functions, exploration-exploitation, model-based RL, reward shaping, and sim-to-real transfer.
• Data-driven mindset: comfortable building experiment pipelines, analyzing training runs, and letting metrics guide architectural decisions.

Nice To Haves

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

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, including improving the simulator itself.
• Build and maintain distributed training infrastructure in JAX across large compute clusters.
• Build agentic optimization systems that automatically improve code, run experiments, analyze metrics, and iterate on RL policies with minimal human intervention.

Benefits

• a 401(k) plan with employer matching
• 16 weeks of paid parental leave
• wellness benefits
• commuter benefits match
• paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act)
• medical, dental, and vision benefits
• 11 paid holidays
• disability and basic life insurance
• family-forming assistance
• a mental health program

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree