- Robot type
- Autonomous Vehicle · Defense
- Location
- SeattleWashingtonUSA
- Job type
- Software
- Posted
- Aug 21, 2026
Full-time
Software Engineer - Planning
Job description
Role Summary: We are seeking a Software Engineer - Planning to design and implement navigational planning algorithms in complex off-road and on-road terrain for unmanned ground vehicles using local sensing. These systems must perform in punishing terrain: understanding how to balance fidelity and optimality against computational efficiency and robustness is a must for high-speed movement. The ideal candidate has experience with both classical and learned approaches to solving planning problems under uncertainty, experience with unmanned ground vehicles, and an understanding of both the benefits and limitations of prior maps.
Job responsibilities
- Design and implement planning algorithms for navigating autonomous ground vehicles through complex off-road terrain.
- Interact frequently with perception and control teams to create shared solutions to challenges. 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.
Job requirements
- Bachelor's degree in computer science, engineering, or related discipline and 5+ years of relevant experience; OR 3+ years of relevant professional experience with an advanced degree.
- Development experience developing production grade software in Python or C++.
- MS degree or PhD preferred.
- Experience creating planning algorithms to handle changing and uncertain environments for mobile robots.
- Experience designing systems to work in GPS Denied, Degraded, Intermittent, and Limited (DDIL) environments.
- Experience with offroad planning for unmanned ground vehicles.
- Experience with on-road planning in structured environments.
- Experience working with and / or incorporating opportunistic prior mapping data.