Autonomy Motion Planner for UAVs (3D Path)

Applied Intuition; Poway (CA); On-site; USD 150,000 - 200,000; Full time

Job summary

Applied Intuition in Poway, CA is seeking an Autonomy Engineer to advance core path planning for multiple aerial platforms. You will develop, integrate, and test autonomy software and GNC components, collaborating across teams and with DoD stakeholders to enable secure military-grade capabilities.

You will work on 3-5 years experience in autonomous planning, implement in C++ or Python, and contribute to robust, modular architectures tested on real systems and simulators.

Qualifications

• 3-5 years of professional experience in autonomous vehicle motion planning, robotics, or a related field.
• Experience in 3D+ path planning using sampling based methods such as RRT* or similar.
• Experience in 2/2.5D grid based planning methods such as A* or similar.
• Experience developing autonomy algorithms in C++ or Python
• Experience developing or implementing outer-loop control systems
• Strong functional, procedural, data-oriented, and object-oriented programming experience
• Experience using git, Visual Studio Code, and GitLab

Responsibilities

• Write software that operates real autonomous aircraft systems including fighter aircraft, maritime vessels, UAVs, and simulators.
• Build and improve aerial autonomy software architectures deployed on real systems to accomplish missions.
• Collaborate with DoD domain experts and vendors to develop and integrate autonomy software onto hardware

Skills

Autonomy algorithms

Path planning

C++/Python

GitLab/VS Code

Tools

Docker

Linux

GitLab

Job description

Applied Intuition in Poway, CA is seeking an Autonomy Engineer to advance core path planning for multiple aerial platforms. You will develop, integrate, and test autonomy software and GNC components, collaborating across teams and with DoD stakeholders to enable secure military-grade capabilities.

You will work on 3-5 years experience in autonomous planning, implement in C++ or Python, and contribute to robust, modular architectures tested on real systems and simulators.