Description
NVIDIA's Autonomous Vehicles Platforms Organization is seeking experienced System Software Engineers to join the Autonomous Vehicles Fleet Engineering Integration team. The successful candidate will work closely with outstanding engineers across different facets of the core platform and AV functions that power NVIDIA's system software stack behind autonomous vehicles.
The role involves engineering the integration of core system software with AV functions software to deliver an outstanding AV Platform to internal and external customers. The position requires collaboration with multiple engineering groups, including sensors, HMI, sensor data recorders, and high-speed storage solutions.
Key responsibilities:
- Participate in and lead engineering collaborations to drive system bring-ups of sophisticated vehicle hardware/software stacks
- Lead the productization of components into fleet-scale production by crafting and advocating measurable engineering metrics
- Debug complex problems across sensors, networks, perception, and core underlying OS
- Lead the left-shifting of tests into HIL and SIL platforms
- Conceptualize, architect, and productize software tools stemming from root cause analysis of system and operational components
Requirements:
- BS or MS degree in EE/CS or a closely related field
- 5+ years of experience in the relevant field
- Excellent programming skills in C++, C, and Python
- Knowledge of system programming, threading, mutex, synchronization, communication, and parallel computing
- Strong debugging abilities in highly pipelined software stacks
- Engineering leadership skills across cross-matrixed organizations
Preferred qualifications:
- Experience in Automotive Vehicle and/or Robotic System fleet management systems
- Demonstrated past experience in software integration across sophisticated software stacks
- Knowledge of Linux, QNX, Android, and/or other real-time operating systems
- Experience with low-latency, highly performant code
- Understanding of system architectures and performance and stability improvements across CPU/GPU/Memory/Storage