Software Engineer, C++ (Onboard Platform)
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 applied.co.
We are an in-office company, and our expectation is that full-time 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 earlier when needed to accommodate family commitments. This in-office expectation does not apply to contractor positions
About the role
Applied Intuition is building Level 4 autonomous technology for vehicles deployed around the world. The reliability of the L4 system is a key element for our autonomy program, and a must-have to safely enable driverless operations on public roads. In the rare case where the system has a hardware or software problem, it needs to be able to detect it and safely bring the vehicle to a safe state if that happens. To achieve this level of reliability and safety, every component of the stack needs to be built to meet the highest quality bar, and that is especially true for the platform layer at the base of the entire system.
Our team builds the foundation of the Level 4 stack, starting with autonomous trucks. We sit between the autonomy algorithms and the vehicle, and we work with every team in the program to take the fleet from supervised testing to driverless operation. Your work will run on real trucks on public roads, and it will be measured by how far the fleet drives between failures.
At Applied Intuition, you will
Shape how Level 4 autonomy and physical AI reach the real world, with software that runs on vehicles on public roads.
Design the runtime architecture of the onboard stack: how processes are scheduled, how they communicate, and how the system degrades when a component fails.
Combine state-of-the-art AI and classical modules to meet the high performance and high reliability requirements
Trace on-road failures from an application symptom to its root cause in the kernel, the hardware, or the middleware, and fix it.
Make a real-time system faster and more predictable on production compute, and prove it with measurements.
Decide how the platform detects and escalates faults, up to commanding the truck to pull over safely.
Build the measurement systems that tell the whole program whether the stack is getting faster and more reliable.
Bring the Applied Intuition self-driving stack up on new compute platforms and new vehicles.
Work alongside some of the strongest engineers in autonomy across perception, planning, controls, hardware, and safety, and set broad, cross-functional technical direction with them.
We're looking for someone who has
Bachelor's in Computer Science, Computer Engineering, or related field.
4+ years of experience shipping complex software in C++14 and above.
Strong system design and engineering fundamentals.
Experience leading the design of a system, from design document through production.
Working knowledge of operating system internals, such as scheduling, memory management, threading, and inter-process communication.
Experience debugging problems that cross the boundary between application code, the operating system, and hardware.