Autonomous Ground Vehicle Trajectory Engineer

Overland AI; Seattle (WA); On-site; USD 160,000 - 230,000; Full time

Benefits offered by this job

Equity compensation

Best-in-class healthcare, dental, and

vision plans

Flexible PTO

401(k) with company match

Paid parental leave

Job summary

Overland AI in Seattle, WA is seeking a Software Engineer – Trajectory Optimization to design and implement planning algorithms for unmanned ground vehicles operating off-road and on-road, using local sensing to balance fidelity and computational efficiency.

You will work on model predictive control and system identification, collaborating across teams to integrate new planning methods, with opportunities to contribute to field tests and product evaluation.

Qualifications

• Bachelor's degree in computer science, engineering, or related discipline with 5+ years of experience, or 3+ years with an advanced degree.
• Production-grade software development experience in Python or C++.

Responsibilities

• Design and implement local trajectory optimization algorithms for autonomous ground vehicles.
• Support rapid integration and adjustment of planning algorithms for a wide variety of vehicles and sensing modalities.
• Work closely with other teams on software development of a shared codebase.
• Leverage a significant corpus of offroad driving data to improve and backstop performance via regression and progression testing.
• Participate in field tests and demonstrations / events for product testing and evaluation.

Skills

Python

C++

Motion planning

Software development

Education

Bachelor's degree in computer science, engineering, or related discipline

MS/PhD preferred

Job description

Overland AI in Seattle, WA is seeking a Software Engineer – Trajectory Optimization to design and implement planning algorithms for unmanned ground vehicles operating off-road and on-road, using local sensing to balance fidelity and computational efficiency.

You will work on model predictive control and system identification, collaborating across teams to integrate new planning methods, with opportunities to contribute to field tests and product evaluation.