- 15+ years of experience in system software, platform firmware, or large-scale distributed systems engineering. BS or MS in Computer Science, Electrical Engineering, or related field (or equivalent experience)
- Deep understanding of rack-scale system software challenges: multi-component coordination, error propagation, health monitoring, and serviceability / reliability
- Experience with fabric management software, cluster management, or system-level orchestration frameworks. Familiarity with firmware architectures and update lifecycle management (multi-component update sequencing, rollback, recovery)
- Understanding of error handling and recovery design patterns in distributed systems — fault isolation, retry policies, graceful degradation
- Experience with health monitoring and telemetry systems: health scoring, event correlation, API design for fleet-level observability
- Understanding of GPU or accelerator system software (drivers, device management, power management) is a strong plus
- Customer obsession – genuine passion for understanding how CSPs operate sophisticated systems at fleet scale and simplifying their experience
- Proven success providing technical leadership across organizational boundaries and influencing system software design without direct authority. Strong communication — ability to translate complex system software architecture into actionable mentorship for customer engineering teams
Ways to stand out from the crowd
- Experience with NVIDIA NVSwitch, NVOS, or GPU fabric management software
- Background in system software for large-scale clusters at a hyperscaler (cluster management, fleet orchestration, health platforms)
- Experience crafting error handling and recovery frameworks for multi-component systems (hundreds or thousands of coordinating devices)
- Familiarity with GPU or accelerator fleet operations — driver lifecycle, firmware rollout strategies, health-based scheduling
- Understanding of how system software decisions impact serviceability, availability, and operational cost at fleet scale
NVIDIA’s invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world.
Are you ready to change the next generation of computing? Join us at the forefront of technological advancement.
NVIDIA data center systems, such as DGX and HGX, have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. These platforms bring together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.