1

Gpu Compiler Engineer Jobs in Utah (NOW HIRING)

GPU Kernel Engineer

Redmond, UT · On-site

$60K - $148K/yr

GPU Kernel Engineer City: Redmond State/Province: Washington Posting Start Date: 8/6/26 Wipro ... Experience with compiler optimizations and runtime execution models * Familiarity with custom SDKs ...

Gpu Compiler Engineer information

What is a GPU compiler engineer?

GPU Compiler Engineers are specialized software engineers who design, develop, and optimize compilers that translate high-level programming code into machine code that runs efficiently on Graphics Processing Units (GPUs). Their work enables developers to harness the full power of GPUs for tasks such as graphics rendering, scientific computing, and machine learning. These engineers often work closely with hardware teams to ensure compatibility and performance, and they play a critical role in advancing GPU technology.

What are some common challenges faced by GPU compiler engineers in optimizing code for different hardware architectures?

GPU Compiler Engineers often encounter challenges when adapting and optimizing code for a wide variety of GPU architectures. Each hardware platform may have unique instruction sets, memory hierarchies, and performance characteristics, requiring tailored compiler optimizations. Balancing performance, portability, and correctness is an ongoing challenge, especially when supporting multiple vendors or generations of hardware. Close collaboration with hardware engineers and performance analysts is essential to ensure the compiler produces efficient code that leverages the strengths of each GPU architecture.

What are the key skills and qualifications needed to thrive as a GPU compiler engineer, and why are they important?

To thrive as a GPU Compiler Engineer, you need a strong background in computer science, with expertise in compiler design, parallel programming, and GPU architectures, typically supported by a relevant degree. Familiarity with tools and languages such as LLVM, CUDA, OpenCL, and performance profiling systems is essential. Analytical thinking, problem-solving ability, and effective collaboration are crucial soft skills for success in this role. These skills ensure the development of high-performance, reliable compiler solutions that optimize GPU-based applications and support innovation in computing.

What is the difference between Gpu Compiler Engineer vs Gpu Software Engineer?

AspectGpu Compiler EngineerGpu Software Engineer
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related; knowledge of compiler designBachelor's or Master's in Computer Science or related; strong programming skills
Work EnvironmentResearch and development teams focused on compiler optimization and hardware integrationSoftware development teams working on GPU applications, drivers, or SDKs
Industry UsagePrimarily in hardware and compiler companies, GPU manufacturers

The Gpu Compiler Engineer specializes in developing and optimizing compilers for GPU hardware, focusing on translating high-level code into efficient machine instructions. In contrast, the Gpu Software Engineer works on creating GPU-related software, such as drivers, SDKs, or applications. While both roles require strong programming skills and knowledge of GPU architecture, the compiler engineer emphasizes compiler design and optimization, whereas the software engineer focuses on software development and integration.

What are popular job titles related to Gpu Compiler Engineer jobs in Utah?

For Gpu Compiler Engineer jobs in Utah, the most frequently searched job titles are:

What cities in Utah are hiring for Gpu Compiler Engineer jobs?

Cities in Utah with the most Gpu Compiler Engineer job openings:

Infographic showing various Gpu Compiler Engineer job openings in Utah as of July 2026, with employment types broken down into 7% As Needed, 87% Full Time, 5% Part Time, and 1% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Senior Compiler Engineer Infrastructure

Socket.dev

Santa Clara, UT • On-site

$170 - $225/hr

Other

Posted 3 days ago

New


Job description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world

We are looking for an experienced Compiler Infrastructure Engineer to join our Compute Compiler Team, with a primary focus on aligning NVIDIA’s compiler codebases with open-source ecosystems and improving developer productivity at scale.

This role sits at the intersection of open-source compiler development, internal compiler infrastructure, and developer experience. You will play a central role in reconciling downstream compiler repositories with upstream open-source projects such as LLVM, Clang, and MLIR, while building the tooling, workflows, and infrastructure that enable compiler engineers across NVIDIA to move faster and with higher confidence. Our compiler organization makes its mark on every GPU NVIDIA produces. By improving how our internal compiler stacks align with open source and by modernizing the tools our developers rely on, you will help ensure that NVIDIA continues to lead in scalable, maintainable, and community‑driven compiler technology. If you are passionate about open-source stewardship, large-scale codebase alignment, and using modern tooling (including AI-assisted workflows) to improve developer velocity, we would love to hear from you.

What you will be doing:
  • Reconcile and synchronize downstream compiler codebases with open-source repositories, including restructuring, refactoring, and upstreaming internal changes where appropriate
  • Lead efforts to restructure, merge, or retire internal code to reduce divergence from upstream open-source projects
  • Design and build infrastructure, tooling, and developer workflows that improve productivity, correctness, and maintainability for internal compiler engineers
  • Develop automation and developer tools to aid in rebasing, patch management, validation, and large-scale refactoring
  • Explore and apply AI-assisted tools to improve developer workflows, including code navigation, change analysis, refactoring assistance, testing, and review efficiency
  • Partner with compiler developers, architecture teams, and CI/test infrastructure teams to ensure changes scale across geographically distributed organizations
  • Serve as a technical bridge between internal compiler development and open-source ecosystems, helping shape long-term alignment strategies
What we need to see:
  • B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, or related field (or equivalent experience)
  • Experience with open-source compiler frameworks
  • Excellent hands‑on C++ programming skills
  • 3+ years experience working with large-scale, long-lived codebases, including refactoring and restructuring efforts
  • Solid understanding of compiler internals, including IRs, passes, build systems, and toolchains
  • Familiarity with source‑control–heavy workflows (e.g., downstream vs. upstream repos, patch queues, rebasing strategies)
  • Strong software engineering fundamentals with an emphasis on robust, maintainable developer infrastructure
  • Good communication and documentation skills; ability to collaborate across teams and time zones
Ways to stand out from the crowd:
  • Direct experience reconciling or maintaining downstream forks of open-source projects
  • Experience building developer productivity tools, CI infrastructure, or large-scale automation
  • Practical experience applying AI or ML‑based tools to improve engineering workflows
  • Background in GPU programming, CUDA, or parallel programming models
  • Familiarity with deep learning frameworks and performance‑sensitive workloads on NVIDIA GPUs

With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 14, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

#J-18808-Ljbffr