Nvidia Senior System Software Engineer - Performance 

United States, Texas 

390810075

NVIDIA is searching for a highly motivated, technical engineer to join the Tegra system-on-chip (SoC) software organization. You will work on key aspects of our ARM SW ecosystem and system software architecture. With a targeted charter to enable best-in-class datacenter-scale performance and efficiency for our next generation of datacenter products, including CPUs and CPU+GPU Superchips.

What you’ll be doing:

• Design, develop, test, and optimize software for our next-generation SoCs. In both pre-silicon and post-silicon phases of execution.

• Review architectural performance bottlenecks for various system wide workloads. Identify HW/SW policies to drive performance and performance/watt leadership.

• Using strong communication skills, build and drive architecture, analysis documents and communications to internal and/or external audiences about our technology.

• Competitive analysis comparing uArchitecture & workload performance metrics on NVIDIA's ARM SoCs against emerging processors from other silicon vendors.

• Influence and drive full-stack adoption of performance optimizations and best practices across NVIDIA SW products & OSS SDKs

What we need to see:

• BS or MS degree in Computer Engineering, Computer Science, or related degree (or equivalent experience).

• 5+ years of relevant computer architecture or SW development experience.

• Proven leadership skills and strong ownership on past projects.

• Hands on technical experience and demonstrated excellence in an environment with complex software and hardware designs.

• Strong understanding of multicore hardware, operating systems design, concurrency, virtual memory, caching, interrupts, device drivers and real-time programming.

• Strong stills in performance analysis, data analysis and performance optimization.

Ways to stand out from the crowd:

• Deep expertise in ARM architecture and SW ecosystem.

• Proficient in analyzing, debugging and tuning performance of complex system software stacks.

• Experience with CPU server system workloads and performance analysis.

• Familiarity with CUDA programming and/or GPUs.

• Experience with HPC or large scale computing environments.