Robotic Hardware Engineer

About Applied Intuition

Applied Intuition, Inc. is powering the future of physical AI. Founded in 2017 and now valued at $15 billion, the Silicon Valley company is creating the digital infrastructure needed to bring intelligence to every moving machine on the planet. Applied Intuition services the automotive, defense, trucking, construction, mining, and agriculture industries in three core areas: tools and infrastructure, operating systems, and autonomy.

Eighteen of the top 20 global automakers, as well as the United States military and its allies, trust the company’s solutions to deliver physical intelligence. Applied Intuition is headquartered in Sunnyvale, California, with offices in Washington, D.C.;
San Diego;
Ft. Walton Beach, Florida;
Ann Arbor, Michigan;
London;
Stuttgart;
Munich;
Stockholm;
Bangalore;
Seoul; and Tokyo. Learn more at

We are an in‑office company, and our expectation is that employees primarily work from their Applied Intuition office 5 days a week. However, we also recognize the importance of flexibility and trust our employees to manage their schedules responsibly. This may include occasional remote work, starting the day with morning meetings from home before heading to the office, or leaving early when needed to accommodate family commitments.

As a Robotics Hardware Engineer at Applied Intuition, you will serve as the primary technical link between hardware design, GNC, and software teams to deliver integrated, flight‑ready systems. You will lead the critical hardware‑software bring‑up process, driving initial validation of flight systems from the bench to the airfield while defining seamless communication interfaces across flight controllers and ground stations. In this role, you will architect repeatable verification workflows and high‑fidelity simulation environments, including Hardware‑in‑the‑Loop (HIL) and Software‑in‑the‑Loop (SIL), to enable rapid iteration and reduce development cycle times.

By setting standards for hardware abstraction and building custom real‑time monitoring tools, you will ensure the delivery of robust, scalable, and maintainable flight software for next‑generation autonomous machines.

• Lead the hardware‑software bring‑up process, driving initial integration and validation of flight systems from the bench to the airfield.
• Deliver integrated, flight‑ready systems by bridging the gap between autopilot firmware, onboard compute, and peripheral vehicle hardware.
• Define and control system interfaces across flight controllers, payloads, and ground stations to ensure seamless communication and data integrity.
• Make critical system‑level tradeoffs between embedded software performance, autonomy requirements, and physical hardware constraints.
• Design and scale automated test frameworks, including high‑fidelity Hardware‑in‑the‑Loop (HIL) and Software‑in‑the‑Loop (SIL) environments with realistic sensor and vehicle simulation.
• Architect repeatable verification workflows that enable rapid iteration and reduce the cycle time from code change to validated flight behavior.
• Build custom tooling for real‑time monitoring and post‑flight analysis to convert complex test data into actionable system improvements.
• Serve as the technical authority for integration and verification, acting as the primary link between hardware design, GNC, and software teams.
• Support flight test campaigns as a hands‑on technical lead, troubleshooting integration issues and ensuring mission success.
• Set the standards for design patterns and hardware abstraction to ensure robust, scalable, and maintainable flight software.

• Degree:
  Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, or a related technical field.
• 5+ years of experience in robotics hardware integration, embedded systems, or aerospace engineering.
• Deep expertise in vehicle electronics integration, specifically bridging autopilot firmware (e.g., PX4, Ardu Pilot) with onboard compute (e.g., NVIDIA Jetson, Raspberry Pi) and peripheral sensors.
• Strong proficiency in C++ and Python, with experience writing hardware abstraction layers…