Robotic Systems & Integration Engineer

Applied Intuition is the vehicle intelligence company that accelerates the global adoption of safe, AI-driven machines. Founded in 2017 and now valued at $15 billion following its recent Series F funding round, Applied Intuition delivers the Vehicle OS, Self-Driving System, and toolchain to help customers build intelligent vehicles and shorten time to market. 18 of the top 20 global automakers and major programs across the Department of Defense trust Applied Intuition's solutions to deliver vehicle intelligence.

Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries and is headquartered in Mountain View, CA, with offices in Washington, D.C., San Diego, CA, Ft. Walton Beach, FL, Ann Arbor, MI, London, Stuttgart, Munich, Stockholm, Bangalore, Seoul, and Tokyo. Learn more at  .

Epi Sci, an Applied Intuition company, develops next-generation, tactical autonomy solutions for national security problems. Epi Sci’s autonomy software is technology agnostic, operationally informed, tactically relevant, and has piloted swarms of uncrewed aerial systems and tactical fighter aircraft. Additional applications include crewed-uncrewed teaming for air dominance, cognitive sensors, and networks for advanced communications systems, as well as battle management command and control for informed decision-making.

Epi Sci delivers unmatched speed, cost-efficiency, and scalability as the preferred partner for defense agencies and industry teams seeking mission-critical autonomy solutions.

As a Systems Engineer on the Battle Management Command and Control team at Epi Sci, your role is critical. You'll deploy and validate software on hardware platforms, focusing on autonomous vehicles or robotics. This position requires both field and office-based work, with significant time spent deploying and testing software on autonomous vehicles in real-world environments.

• System Engineering:
  Develop, deploy, and validate software systems on autonomous vehicles, focusing on robotics, sensors, and vehicle autopilots
• Field Deployment & Testing:
  Participate in hands‑on fieldwork, deploying software on vehicles and ensuring proper functionality in dynamic, real‑world environments
• 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
• 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
• Communication Systems:
  Address inter‑vehicle, ensuring seamless data exchange between vehicles for collaborative autonomous operations
• Third‑Party Software Integration:
  Interface with and integrate third‑party software and APIs into our systems
• Software Quality & CI/CD:
  Work on software integration, Continuous Integration/Continuous Deployment (CI/CD) processes, and implement system‑related improvements to enhance system performance and reliability
• Simulation & Testing:
  Leverage simulation environments to test vehicle systems, validating software behavior in various scenarios before field deployment
• Collaboration & Documentation:
  Collaborate with cross‑functional teams, including software engineers, data scientists, and field operators, to ensure the successful deployment of systems. Document processes and provide updates on system status and improvements

• 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++
• Hands‑on experience with robotic systems, sensors (such as RADAR, cameras, radar), and vehicle autopilots (e.g., PX4, ROS)
• Familiarity with AI frameworks (Tensor Flow, PyTorch, OpenCV, etc.) and perception pipeline development
• Experience with CI/CD tools such as Jenkins, Git Lab, or similar tools for automating deployments and testing
• Knowledge of…