System Software Engineer Intern, Autonomous Vehicles - 2027

NVIDIA is the engine of the AI era. We invented the GPU, and the accelerated computing it made possible now powers the world's most advanced AI, from the data center to the car. Today, NVIDIA DRIVE brings that intelligence to the road: a full-stack platform that lets vehicles perceive, reason and act in the real world. We are looking to grow our teams with the smartest people in the world, and there has never been a more exciting time to join us. The Autonomous Vehicles team develops and ships NVIDIA's DRIVE software platform. Our AV Stability group owns the reliability of the full stack on real vehicles: every issue found on a test drive flows through us before it reaches the owning team. You will reproduce, investigate and help fix the problems that stand between a prototype and a product, working with sensor, perception, planning and platform teams across the globe. As AI reshapes how engineering itself is done, our team is also where that change meets the vehicle: we increasingly build intelligent tooling on top of the same expertise we use to debug the car. We have real customers and real competition, and the work is exciting, fun, and very meaningful. What you'll be doing: Use in-house data playback, simulation, and visualization tools to re-animate and reproduce performance issues experienced during test drives. Collaborate with software and algorithm experts to investigate, deduce, and isolate root causes of test drive issues, and to develop fixes and improvements. Design and implement Autonomous Vehicles software, including system integration, application design, performance/power optimization, and stress/stability/compliance testing. Drive the reliability of the whole software system, including time sync, vehicle network, RADAR, LiDAR, and camera sensor processing, and fusion. Help turn hard-won debugging expertise into tooling and automation, including AI-assisted analysis of logs and vehicle data, so that problems are found faster and recur less. Develop a strong technical understanding of the stack, and proactively identify new opportunities and creative ways to solve or mitigate technical challenges. What we need to see: Pursuing a BS or MS in CS/CE/EE/Robotics or a related field. Demonstrated proficiency in both C/C++ and Python: C/C++ to understand and debug the vehicle software stack, Python to build the tooling around it. Strong debugging instincts: you can read logs and traces, form a hypothesis, and prove or disprove it with evidence. Ability of using modern AI coding assistants as part of your everyday workflow, while verifying what they produce. Familiar with git or other version control tooling. Ability and flexibility to work and communicate effectively in a multinational, multi-time-zone environment. Self-motivated and a good teammate. Ways to stand out from the crowd: Good knowledge of key Autonomous Driving technologies and the typical challenges of key components; prior experience in the AV field. Worked with CAN and related tools, RADAR, LiDAR. Hands-on experience with LLM-based tooling: prompt and context design, tool calling, agent workflows, or evaluation of model output on a real task. Experience with large-scale log analysis and cloud-based workflows.