System Software Engineer, GPU Development Tools

Job Description

A key part of NVIDIA's strength is our sophisticated development tools and modelling environments that enable our incredible pace of delivering new technology to market. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high production-quality standards. This software engineering role involves developing high-level chip models, test APIs and trace generation workflows, and analysis tools.
As a member of the software development team, you will engineer and improve the core infrastructure for execution, automation, and debugging the development of large-scale, general-purpose graphics and computing chips. This infrastructure enables our driver stack, applications, tests, and studies to run unchanged on all functional, diagnostic, and performance models.
What you'll be doing:

  • This role will require you to play a critical part in every stage of development of a GPU!

  • Improve the daily workflows of the world's top chip modelers and designers to help produce the next greatest generation of GPUs.

  • Empower GPU architects to understand application performance today and model competition-destroying performance for tomorrow.

  • Coordinate with architecture and software teams to enable functional and performance testing for the next architecture.

What we need to see:

  • Bachelor's or higher degree in Computer Science or Computer Engineering

  • Strong C++, or Java and JavaScript programming capability

  • Ability to work across the GPU, driver, and application stacks

  • Some familiarity with a scripting language, such as Python

  • Excellent interpersonal skills

  • Flexibility for working in an evolving environment with different frameworks and requirements

Ways to stand out from the crowd:

  • Know-how working on operating system kernels or writing device drivers with strong systems-level debugging skills

  • A knowledge of GPU APIs such as DirectX, CUDA, Vulkan or OpenGL

  • Experience with chip and/or system simulation

  • Experience in performance analysis of sophisticated systems

  • Deep understanding of systems architecture: CPU, GPU, memory, display, buses, kernel internals would be advantageous




NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — 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, NVIDIA is increasingly known as 'the AI computing company.

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