Autonomy Integration Software Engineer

Applied Intuition Applied Intuition · Robotics · Ann Arbor, MI · Government

Software Engineer role focused on integrating and deploying autonomy systems for physical AI applications in robotics, automotive, and defense. The role involves developing, testing, and maintaining software for autonomous vehicles, including sensor integration, perception pipelines, inter-vehicle communication, and simulation. Requires strong programming skills in Python/C++, experience with robotic systems, and CI/CD.

What you'd actually do

  1. Systems Engineering: Develop, deploy, and validate software systems on autonomous vehicles, focusing on robotics, sensors, and vehicle autopilots
  2. Field Deployment & Testing: Participate in hands-on fieldwork, deploying software on vehicles and ensuring proper functionality in dynamic, real-world environments
  3. Interfacing with Sensors and Autopilots: Work directly with sensors (e.g., RADAR, cameras, GPS, SONAR) and vehicle autopilot systems, integrating them into the autonomous vehicle framework
  4. Perception & Autonomous Modules: Work with the Perception and Autonomy teams to deploy and optimize perception pipelines (Vision, Radar, Fusion) and vehicle autonomy SW, ensuring robust and safe vehicle operation
  5. Communication Systems: Address inter-vehicle communication, ensuring seamless data exchange between vehicles for collaborative autonomous operations

Skills

Required

  • MS or PhD in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or equivalent OR 5 years of relevant experience designing multi-agent autonomy
  • Strong proficiency in Linux and command-line tools
  • Strong proficiency in Python and/or C++ (most work is in C++)
  • Hands-on experience with robotic systems, sensors (such as RADAR, cameras, radar), and vehicle autopilots (e.g., PX4, ROS)
  • Experience with CI/CD tools such as Jenkins, GitLab, or similar tools for automating deployments and testing
  • Knowledge of communication protocols for inter-vehicle communications (e.g., DDS, UDP, ROS2, etc.)
  • Experience in integrating third-party software and APIs
  • Must be a U.S. Citizen
  • Must hold or be eligible to obtain and maintain a U.S. security clearance

Nice to have

  • Ability to work in field environments, troubleshooting, testing, and deploying systems in challenging conditions
  • Excellent communication skills, both written and verbal, with the ability to document processes and communicate technical concepts to cross-disciplinary teams
  • Ability to work in a fast-paced, evolving environment, as well as working under challenging conditions in remote or field locations
  • Familiarity with maritime vessels and/or airborne drones

What the JD emphasized

  • Integration with new vehicles and hardware is a critical function
  • significant time spent deploying and testing software on autonomous vehicles in real-world environments
  • deploying and testing software on autonomous vehicles in real-world environments
  • deploy software on vehicles
  • deploy and optimize perception pipelines
  • deploying systems

Other signals

  • Develop, deploy, and maintain the backbone of all-domain autonomy capabilities
  • Integration with new vehicles and hardware is a critical function
  • deploying and testing software on autonomous vehicles in real-world environments
  • Develop, deploy, and validate software systems on autonomous vehicles, focusing on robotics, sensors, and vehicle autopilots
  • Work directly with sensors (e.g., RADAR, cameras, GPS, SONAR) and vehicle autopilot systems, integrating them into the autonomous vehicle framework
  • Work with the Perception and Autonomy teams to deploy and optimize perception pipelines (Vision, Radar, Fusion) and vehicle autonomy SW, ensuring robust and safe vehicle operation
  • Address inter-vehicle communication, ensuring seamless data exchange between vehicles for collaborative autonomous operations
  • Leverage simulation environments to test vehicle systems, validating software behavior in various scenarios before field deployment
  • MS or PhD in Robotic Engineering, Computer Science, Computer Engineering, Optimization, or equivalent OR 5 years of relevant experience designing multi-agent autonomy