Job description

The Autonomous Vehicles Platform team is seeking a Senior System Software Engineer to help bring NVIDIA's autonomous vehicle platform to new markets! This role involves developing and productizing innovative solutions that will transform transportation and the field of self-driving cars. What you'll be doing: • Drive end-to-end software bring-up for next-generation NVIDIA DRIVE autonomous vehicle platforms — from hardware power-on through production-ready system deployment, across OS, middleware, and application layers. • Build and evolve agentic AI tools and frameworks to accelerate bring-up, improve efficiency, and enable the scaling of new platforms. • Lead cross-functional teams through system-level debugging and optimization across complex embedded hardware-software ecosystems. What we need to see: • BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience). • 5+ years of demonstrated success in designing and implementing complex system software. • Deep domain expertise in embedded systems architecture, specifically hardware-software co-design, integration, and platform bring-up. • Expertise in low-level debugging and system-level optimization within complex embedded hardware-software ecosystems. • Proven ability to drive technical alignment across organizational boundaries, synthesizing system-wide requirements from multiple stakeholders. • Strong communicator who can operate effectively across global, fast-paced teams. • A results-driven mindset to solving ambiguous technical challenges. Ways to stand out from the crowd: • Experience navigating and debugging within large-scale embedded OS codebases (e.g., BSP, middleware layers) across complex SoC platforms. • Demonstrated track record of building agentic AI tools or LLM-driven workflows that accelerate bring-up and reduce integration cycle time. • In-depth domain expertise in automotive networking protocols (Ethernet, CAN/CAN-FD, LIN) and real-time communication middleware. We value different paths to technical excellence and welcome candidates who bring strong judgment, curiosity, and a collaborative approach. Come build the future of autonomous vehicle simulation with us!

Requirements

Must-haves

Drive end-to-end software bring-up for next-generation NVIDIA DRIVE autonomous vehicle platforms — from hardware power-on through production-ready system deployment, across OS, middleware, and application layers.
Build and evolve agentic AI tools and frameworks to accelerate bring-up, improve efficiency, and enable the scaling of new platforms.
Lead cross-functional teams through system-level debugging and optimization across complex embedded hardware-software ecosystems.
BS or MS in Computer Science, Computer Engineering, or a related field (or equivalent experience).
5+ years of demonstrated success in designing and implementing complex system software.
Deep domain expertise in embedded systems architecture, specifically hardware-software co-design, integration, and platform bring-up.
Expertise in low-level debugging and system-level optimization within complex embedded hardware-software ecosystems.
Proven ability to drive technical alignment across organizational boundaries, synthesizing system-wide requirements from multiple stakeholders.
Strong communicator who can operate effectively across global, fast-paced teams.
A results-driven mindset to solving ambiguous technical challenges.
Experience navigating and debugging within large-scale embedded OS codebases (e.g., BSP, middleware layers) across complex SoC platforms.
Demonstrated track record of building agentic AI tools or LLM-driven workflows that accelerate bring-up and reduce integration cycle time.
In-depth domain expertise in automotive networking protocols (Ethernet, CAN/CAN-FD, LIN) and real-time communication middleware.
We value different paths to technical excellence and welcome candidates who bring strong judgment, curiosity, and a collaborative approach. Come build the future of autonomous vehicle simulation with us!

Nice-to-haves

None flagged.

Application prep

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