Software Engineer, GPU Design Automation

NVIDIA•Hillsboro, CA

About The Position

NVIDIA's GPU Architecture Group is looking for a software engineer to further modernize and scale GPU development. As GPU designs become more complex, our hardware models, testbenches, build scripts, and code generation flows need to keep adapting to this complexity. The development workflow will be parameterized and data-driven, so it adapts without manual rework. You'll apply modern software engineering techniques, including AI-assisted development, to a hardware domain where these practices can have outsized impact, and help spread those ways of working across a broader team. This role offers a unique opportunity to influence how one of the world's most advanced chips are developed!

Requirements

B.S., M.S., or PhD in Computer Science, Computer Engineering, or a related field (or equivalent experience)
Strong software engineering fundamentals and programming skills(Python, C++, or similar)
Experience with build systems, code generation, or design automation flows
3 years or more experience in relevant roles
Motivation to engage with and refine sizable, complicated codebases — converting legacy systems into maintainable, well-structured infrastructure
Familiarity with hardware development workflows (modeling, verification, or similar)
Up to date with modern software engineering methods including CI and AI-powered tooling
Effective collaboration skills for working across team and functional boundaries (architecture, ASIC, software)

Nice To Haves

Experience building or maintaining hardware build automation infrastructure at scale
Background in parameterized code generation or template driven build systems
Track record of improving developer efficiency through tooling and automation
Familiarity with GPU or ASIC development processes
Experience with configuration management for complex hardware IP

Responsibilities

Design and build automation to scale GPU development processes across hardware models, testbenches, and build systems.
Develop and extend code generation flows that automate configuration and adapt to new designs without manual rework.
Refactor and improve large, complex codebases to be more parameterized, data-driven, and maintainable.
Collaborate with ASIC design and architecture teams to align on automation approaches.
Adapt modern software engineering workflows to GPU architecture development and find opportunities to set a higher standard.
Establish and maintain high standards for software quality and consistency across shared infrastructure.