Software Engineer, C++ (Onboard Platform)
About The Position
Applied Intuition is building Level 4 autonomous technology, starting with autonomous trucks. The team develops the foundation of the Level 4 stack between autonomy algorithms and the vehicle, supporting the transition from supervised testing to driverless operation. The software runs on trucks on public roads, with fleet distance between failures serving as a measure of reliability. The role focuses on the onboard platform layer and the reliability and safety of the autonomy system. It involves designing runtime architecture, improving real-time performance and predictability, diagnosing failures across software and hardware layers, implementing fault detection and escalation, building measurement systems, and bringing the self-driving stack to new compute platforms and vehicles. The engineer works cross-functionally with teams across perception, planning, controls, hardware, and safety, and helps set technical direction.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related field.
- At least 4 years of experience shipping complex software in C++14 or later.
- 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 across application code, the operating system, and hardware.
Nice To Haves
- Experience developing onboard application software in autonomy, ADAS, or robotics.
- Experience with real-time systems, an RTOS, or QNX.
- Experience with robotics middleware or shared-memory communication, such as ROS 2 or DDS.
- Experience with profiling and tracing tools.
- Experience with vehicle hardware and networks such as CAN.
- Experience mentoring software engineers.
- Professional experience with Python.
Responsibilities
- Design the onboard stack runtime architecture, including process scheduling, communication, and system degradation when a component fails.
- Combine AI and classical modules to meet performance and reliability requirements.
- Trace on-road failures from application symptoms to root causes in the kernel, hardware, or middleware, and fix them.
- Improve real-time system speed and predictability on production compute and validate improvements with measurements.
- Determine how the platform detects and escalates faults, including commanding a truck to pull over safely.
- Build measurement systems to track stack performance and reliability.
- Bring the Applied Intuition self-driving stack up on new compute platforms and vehicles.
- Collaborate with engineers across perception, planning, controls, hardware, and safety, and set cross-functional technical direction.
- Design systems from design document through production.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
