Lead Simulation Engineer

DoorDash DoorDash · Consumer · San Francisco, CA · 311 Autonomy

Seeking a Lead Simulation Engineer to architect and build an end-to-end aerial autonomy simulation stack. This role involves owning core architecture decisions, developing key components, setting engineering standards, and mentoring a team. The ideal candidate has experience building simulation systems from first principles and understands simulator internals deeply.

What you'd actually do

  1. Architect and implement an end-to-end simulation stack for aerial autonomy at DoorDash Labs.
  2. Develop high-fidelity simulation capabilities, including:
  3. Design and implement scalable simulation infrastructure to support:
  4. Build cloud-deployed simulation systems to enable large-scale parallel testing and pilot training.
  5. Partner closely with autonomy, controls, and aircraft teams to ensure simulation fidelity and validation alignment.
  6. Establish technical direction, architecture standards, and performance benchmarks for simulation.
  7. Mentor and grow a small team of simulation engineers while remaining deeply hands-on.

Skills

Required

  • Master’s or PhD in Computer Science, Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, or a related field.
  • 10+ years of experience in robotics or physics-based simulation.
  • Deep expertise in simulator internals
  • Experience integrating simulation environments with robotics autonomy stacks.
  • Proven experience architecting complex technical systems from scratch.
  • Demonstrated technical leadership as a Principal Engineer or equivalent senior technical role.
  • Strong system-level thinking with the ability to balance fidelity, scalability, and development velocity.

Nice to have

  • Experience implementing a simulator from scratch (professional or personal projects).
  • Familiarity with modern robotics simulators such as MuJoCo, Gazebo, Isaac, Newton, Genesis, or similar frameworks.
  • Published research in robotics simulation, dynamics, or related areas.
  • Hands-on experience building and operating robotic or UAV systems.
  • Experience with aerospace, UAV flight dynamics, or safety-critical autonomous systems.
  • Experience deploying simulation infrastructure in cloud environments for large-scale distributed testing.

What the JD emphasized

  • architect and build an end-to-end aerial autonomy simulation stack
  • owning core architecture decisions
  • developing key components yourself
  • setting engineering standards
  • built simulation systems from first principles
  • understands simulator internals deeply
  • architect complex technical systems from scratch