Manager, Software Performance Engineering - Autonomous Vehicles

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Manager of Software Performance Engineering for Autonomous Vehicles at NVIDIA, focusing on scaling performance engineering efforts across the NVIDIA DRIVE Autonomous Solutions (NDAS) product portfolio. The role involves leading a team, defining roadmaps, improving workflows, and collaborating with customers and internal teams to ensure high-quality autonomous driving experiences.

What you'd actually do

  1. Define and maintain the strategic execution roadmap, ensuring scalability across diverse product lines, release timelines, emerging customer engagements, and next-generation hardware platforms.
  2. Lead and mentor a team of Performance Engineers in day-to-day execution, driving timely NDAS releases aligned with OEM partner roadmaps.
  3. Improve performance engineering workflows and processes to foster a scalable, organization-wide performance culture.
  4. Partner proactively with OEM customers, algorithm teams, OS, and hardware groups to establish a cohesive long-term architecture and technical vision for NDAS.
  5. Provide regular, transparent communication of program status, risks, and key issues to leadership and multi-functional collaborators.

Skills

Required

  • Software Engineering experience
  • Software team management experience
  • BS or MS degree in Computer Science or related field (or relevant experience)
  • Experience leading successful releases with short release cadence in a dynamic environment
  • Proven ability to understand and collaborate across complex technical SW stacks and their interdependencies in big organizations
  • Proven record of leading and successfully delivering organizational wide programs and projects as well as process improvements

Nice to have

  • Software management or systems engineering experience for large-scale mission/safety critical systems, specifically with autonomous vehicles, avionics or robotics
  • Software performance optimization exposure, especially in Embedded/Real-time Systems, GPU/CUDA optimizations or C++ algorithmic optimizations
  • Strong grasp of Computer Architecture & Operating System concepts
  • Exposure to developing or delivering deep learning projects on Embedded Systems/NVIDIA DRIVE platforms

What the JD emphasized

  • Software management or systems engineering experience for large-scale mission/safety critical systems, specifically with autonomous vehicles, avionics or robotics.