System Software Engineer, GPU Development Tools

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:

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  This role will require you to play a critical part in every stage of development of a GPU!
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  Improve the daily workflows of the world's top chip modelers and designers to help produce the next greatest generation of GPUs.
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  Empower GPU architects to understand application performance today and model competition-destroying performance for tomorrow.
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  Coordinate with architecture and software teams to enable functional and performance testing for the next architecture.

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  Bachelor's or higher degree in Computer Science or Computer Engineering
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  Strong C++, or Java and JavaScript programming capability
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  Ability to work across the GPU, driver, and application stacks
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  Some familiarity with a scripting language, such as Python
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  Excellent interpersonal skills
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  Flexibility for working in an evolving environment with different frameworks and requirements

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  Know-how working on operating system kernels or writing device drivers with strong systems-level debugging skills
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  A knowledge of GPU APIs such as DirectX, CUDA, Vulkan or OpenGL
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  Experience with chip and/or system simulation
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  Experience in performance analysis of sophisticated systems
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  Deep understanding of systems architecture: CPU, GPU, memory, display, buses, kernel internals would be advantageous