Software Engineer - Planning (Sampling / Search)

Applied Intuition•Ann Arbor, MI

1d•Onsite

About The Position

As a Path Planning engineer at Applied, your role is pivotal. Your work will involve developing, integrating, and testing core path planning capabilities that span all classes of aerial platforms (Group 1-5). You'll work closely with teams across the entire company to integrate core GNC algorithms into their software and product stacks, supporting applications in both commercial and defense spaces. The challenge is profound, and the rewards are immeasurable, as you build superior systems that empower our military with unrivaled capabilities.

Requirements

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 either 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, GitLab
Must be willing to travel as projects requires; estimated average travel is once every other month for between 2 days up to 1 week (~20%)
Must be a U.S. Citizen
Must hold or be eligible for a U.S. Secret security clearance

Nice To Haves

Experience with UAS GNC/navigation systems such as PX4 and Ardupilot
Ability to use data visualization and debugging tools to support autonomy control development
Experience developing in Docker and containerized development environments, using Linux-based operating systems (e.g., RHEL, Ubuntu), source control systems, and artifact registries

Responsibilities

Write software that operates real autonomous aircraft systems including fighter aircraft, maritime surface vessels, group 1-5 unmanned aerial vehicles (UAVs), as well as simulated models to accomplish tactical military missions
Build, leverage, and improve aerial autonomy software architectures that are ultimately tested and deployed on real systems to accomplish military missions
Collaborate with DoD warfighter domain experts and 3rd party UAS vehicle vendors to develop and integrate aerial autonomy software onto OEM hardware