Senior System Software Engineer - Av Platform

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Senior System Software Engineer to integrate and productize NVIDIA's autonomous vehicle platform software, collaborating with cross-functional teams and customers to ensure compliance and meet production release timelines.

What you'd actually do

  1. Lead software integration with a systematic approach to streamline embedded development for NVIDIA Drive Autonomous vehicle solution products.
  2. Architect and develop platform software, tools, filesystem customization, with efficient software integration in multiple OS environments with AI powered workflows.
  3. Proactively work with system architects, software/firmware engineers, HW/SW QA teams, and application engineering teams to drive cross-team dependency and schedule alignment, coordinate progress, and debug issues to meet production release timelines.
  4. Regularly engage with customer teams to productize workflows for platform integration.
  5. Collaborate with other engineering teams to enable automated workflows for development, sanity testing, car validation, and software release deliveries.

Skills

Required

  • 8+ years of experience working on software development autonomous vehicles
  • Proficient debugging skills from application to kernel level on embedded hardware
  • Strong communication skills and the ability to collaborate with multiple cross-functional teams
  • Proven expertise in embedded systems, architecture design and SW/HW cross-domain knowledge
  • Ability and flexibility to work and communicate effectively in a multinational, multi-time-zone corporate environment
  • Self-motivated, organized, and proactive

Nice to have

  • Leveraged AI for building small to complex embedded projects to improve platform developer efficiency
  • Experience with Linux and QNX filesystems, and QNX RTOS is a major plus
  • Background in automotive ECU software integration or Prior experience in the automotive field
  • Familiarity with the Bazel build system
  • python programming
  • cloud services
  • Jenkins
  • Docker in continuous integration and deployment systems

What the JD emphasized

  • autonomous vehicles
  • embedded development
  • AI powered workflows
  • production release timelines
  • customer teams
  • automated workflows
  • embedded hardware
  • embedded systems