Senior Motion Planning Engineer — Autonomy

OpenKrill; United States; Remote; USD 199,000 - 292,000; Full time

Benefits offered by this job

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

11 paid holidays

Job summary

DoorDash is seeking a seasoned Senior Planner Engineer to ship production-level autonomy systems with deep expertise in motion planning and trajectory optimization for dynamic environments. You will design and deploy planning algorithms that generate safe, reliable motion plans amid uncertain agent behaviors and real-time constraints.

Ideal candidates will have full lifecycle experience of autonomous products, solving robustness, reliability, and performance challenges, and will serve as a key

Qualifications

• BS/MS/PhD in CS, EE, Robotics, or related field, or equivalent practical experience.
• Strong C++ software engineering experience for production-quality systems.
• Experience developing or deploying motion planning, trajectory optimization, robotics, or real-time decision-making systems.
• Data-driven evaluation, simulation, and performance metrics knowledge.

Responsibilities

• Design and ship real-time behavior and motion planning features for complex urban/suburban driving scenarios.
• Lead automation of root-cause analysis and reduce planner-related disengagements and failures.
• Build scalable evaluation, simulation, and validation frameworks for safe rollout to new regions.
• Collaborate with perception, prediction, controls, and platform teams for end-to-end autonomy improvements.
• Contribute to architecture decisions to improve planner robustness, generalization, and efficiency.

Skills

C++

Motion planning

Trajectory optimization

Robotics

Real-time systems

Education

BS/MS/PhD in CS, EE, Robotics

Job description

DoorDash is seeking a seasoned Senior Planner Engineer to ship production-level autonomy systems with deep expertise in motion planning and trajectory optimization for dynamic environments. You will design and deploy planning algorithms that generate safe, reliable motion plans amid uncertain agent behaviors and real-time constraints.

Ideal candidates will have full lifecycle experience of autonomous products, solving robustness, reliability, and performance challenges, and will serve as a key