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DoorDash USA

Senior/Staff Deep Reinforcement Learning Engineer - DoorDash Dot

DoorDash USA · San Francisco, CA

Posted about 3 months ago

or apply directly on DoorDash USA's site. We never take the application ourselves.

Is this posting real?

This role has been open
103 days
DoorDash USA's roles stay open a median of 103 days
Reposted
No
Salary listed
No
0% of DoorDash USA's roles list one
Ghost-job risk at DoorDash USA
high
462 stale, 8 reposted of 462 open
Hiring momentum
135 roles opened in the last 90 days
↓ down vs. the prior 90 days
Last confirmed on the employer's board
2026-11-14

Measured from postings appearing on and disappearing from DoorDash USA's own greenhouse board since 2026-08-03. Full hiring picture for DoorDash USA.

About this role

As a Senior/Staff Deep Reinforcement Learning Engineer at DoorDash, you will be responsible for designing, training, and deploying deep reinforcement learning policies for autonomous vehicles. Your role involves the full lifecycle of RL policy development, from problem formulation to on-vehicle inference, while working with a stack that utilizes JAX for efficient training and deployment.

Our read on this posting3.2out of 5
benefits
5/5
freshness
1/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of DoorDash USA as an employer.

What you need

  • 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 in the software development lifecycle
  • Hands-on experience training RL agents at scale, ideally in robotics or autonomous driving
  • Proficiency in JAX or a similar functional ML framework
  • Deep grasp of core RL concepts: policy gradients, value functions, exploration-exploitation, model-based RL, reward shaping, and sim-to-real transfer

Nice to have

  • Publications at top venues 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

What you get

  • 401(k) plan with employer matching
  • 16 weeks of paid parental leave
  • Wellness benefits
  • Commuter benefits match
  • Paid time off and paid sick leave
  • Medical, dental, and vision benefits

Worth weighing

  • No specific salary figure provided, only a range
  • The role involves working with a pure JAX stack, which may be a consideration for those with different framework preferences
  • The position requires a strong focus on real-time decision-making, which may not suit all candidates

Summarised from DoorDash USA's posting. Read the full original.

Listed by DoorDash USA on their greenhouse job board, last confirmed open on 2026-11-14. PitchMeAI is not the employer.

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