NVIDIA
NVIDIA
NVIDIA develops accelerated computing and artificial intelligence technologies used across gaming, data centers, cloud computing, healthcare, manufacturing, automotive, and robotics. Its work spans graphics processing units, AI platforms, simulation, and industry-focused solutions, including NVIDIA Omniverse for collaborative 3D workflows, NVIDIA DRIVE for autonomous vehicle development, and NVIDIA Clara for healthcare applications. The company brings together large technical teams working on the infrastructure and software that support advanced computing, simulation, and AI-driven analytics.

NVIDIA Remote System Software Engineer, Performance

Optimize performance for NVIDIA’s next-generation datacenter CPUs and CPU-GPU Superchips built on ARM SoCs. Analyze bottlenecks, benchmarks, and workloads across competing processors.

Description

  • Develop, test, and optimize software for next-generation SoCs before and after silicon is available.
  • Identify and investigate SoC performance bottlenecks.
  • Create analysis documents and communications about NVIDIA technology for internal or external audiences.
  • Compare microarchitecture and workload performance on NVIDIA ARM SoCs with processors from other silicon vendors.
  • Build tools and apply benchmarks to assess performance.

Requirements

  • A bachelor’s or master’s degree in computer engineering, computer science, or a related field, or equivalent experience.
  • At least two years of relevant computer architecture or software development experience.
  • Hands-on technical experience and a record of strong work with complex software and hardware designs.
  • Strong knowledge of multicore hardware, operating system design, concurrency, virtual memory, caching, interrupts, device drivers, and real-time programming.
  • Experience analyzing data and performance, and optimizing performance.
  • Expertise in ARM architecture and its software ecosystem.
  • Proficiency in analyzing, debugging, and tuning performance across complex system software stacks.
  • Experience with CPU server workloads and performance analysis.
  • Familiarity with CUDA programming, GPUs, or both.
  • Experience in high-performance computing or large-scale computing environments.

Benefits

  • Comprehensive benefits package.
  • Equity.
  • Competitive salary.

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