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, Computer Engineering, or related major

• 5+ years of experience

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

• Strong C/C++ is a must-have capability

• Excellent interpersonal skills

• Ability to multi-task

• Some familiarity with a scripting language, such as Python or Perl

• 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

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

• Advanced programming expertise with full-stack web based visualization technologies to help provide data insights.