Senior System Software Engineer - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Shanghai, China

Senior Software Engineer for NVIDIA's Autonomous Vehicles division, focusing on the software foundation for AI-powered ADAS and safety features. The role involves adapting NVIDIA Drive software, triaging and diagnosing complex issues in safety-critical systems, collaborating with teams to find root causes and implement solutions, supporting function bring-up, assessing functional performance, debugging functions, ensuring end-to-end traceability, and coordinating fixes across international teams. Requires strong background in ADAS development and triage, proficiency in Linux/QNX, understanding of ADAS/AD functions, and systematic issue isolation skills. Experience with C++, Python, sensor-based automotive software, ADAS feature validation, SoC architectures, CUDA, TensorRT, GPU computing, and performance bottleneck identification are advantageous.

What you'd actually do

  1. Be responsible for adaptation of NVIDIA Drive software on development and production vehicles.
  2. Triaging, analyzing, and diagnosing complex issues across safety-critical ADAS and autonomous driving systems — from sensor inputs to function-level behaviors.
  3. Collaborate with OEM and NVIDIA teams to root cause software and functional problems, propose immediate solutions as well as long-term corrective actions.
  4. Support NDAS function bring-up activities on the partner vehicle platforms.
  5. Understanding the SW builds, assessing the functional performance from data and understanding the functional issues.

Skills

Required

  • Strong background in ADAS development and triage, with at least 5+ years of experience including in-vehicle activities.
  • Demonstrates strong team spirit, with a clear prioritization of project delivery success.
  • Proficiency in Linux and/or QNX-based embedded environments.
  • Solid understanding of ADAS/AD functions from concept to validation.
  • Demonstrated ability to systematically isolate issues using log analysis, data review, and cross-functional technical coordination.
  • MS in Computer Science, Electrical, or Automotive Engineering (or equivalent practical experience).
  • Excellent communication skills — able to explain technical findings clearly and concisely across engineering teams.
  • Valid driver’s license and readiness for road testing and travel.

Nice to have

  • Advanced programming in C++ and Python.
  • Experience in sensor-based automotive software (camera, radar, lidar, GPS, ultrasound).
  • Hands-on expertise in ADAS feature validation and use-case triaging.
  • Familiarity with SoC-based automotive architectures, CUDA, TensorRT and GPU computing.
  • Proven record of identifying performance bottlenecks and proposing design improvements across perception, fusion, or planning modules.

What the JD emphasized

  • safety-critical ADAS
  • safety-critical ADAS
  • road testing