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Gpu Compiler Engineer Jobs in Renton, WA (NOW HIRING)

Senior AI Compiler Engineer, MLIR

Seattle, WA · On-site

$139K - $183K/yr

More recently, GPU deep learning ignited modern AI - the next era of computing - with the GPU ... NVIDIA is hiring a Senior AI Compiler Engineer. GPUs are driving rapid progress in deep learning ...

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... programming model that shipped with CUDA 13.1, and TensorIR is an open-source compiler ...

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... programming model that shipped with CUDA 13.1, and TensorIR is an open-source compiler ...

Senior LLVM Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

We are seeking for an expert Senior Compiler Engineer to join our Compute Compiler Team, with a ... Background in GPU architectures, CUDA, or parallel programming models * Familiarity with deep ...

Senior LLVM Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

We are seeking for an expert Senior Compiler Engineer to join our Compute Compiler Team, with a ... in GPU architectures, CUDA, or parallel programming models Familiarity with deep learning ...

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and ...

Senior Deep Learning Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and ...

Senior DL Compiler Engineer -CUDA Tile

Redmond, WA · On-site

$137K - $180K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep ...

Senior DL Compiler Engineer -CUDA Tile

Redmond, WA · On-site

$137K - $180K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep ...

Senior DL Compiler Engineer -CUDA Tile

Redmond, WA · On-site

$137K - $180K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep ...

Senior DL Compiler Engineer -CUDA Tile

Redmond, WA · On-site

$137K - $180K/yr

An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can ... We are hiring software engineers for the CUDA Tile team. NVIDIA GPUs are at the center of the deep ...

We are seeking a software engineer to join the MTIA LLVM Compiler team, working on the compiler ... Experience working closely with hardware architectures such as SIMD, GPU, RISC-V, and AI ...

Showing results 21-40

Gpu Compiler Engineer information

See Renton, WA salary details

$12.4K

$93.7K

$127.1K

How much do gpu compiler engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for gpu compiler engineer in Renton, WA is $93,688.00, according to ZipRecruiter salary data. Most workers in this role earn between $39,900.00 and $121,500.00 per year, depending on experience, location, and employer.

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 Renton, WA?

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

What job categories do people searching Gpu Compiler Engineer jobs in Renton, WA look for?

The top searched job categories for Gpu Compiler Engineer jobs in Renton, WA are:

What cities near Renton, WA are hiring for Gpu Compiler Engineer jobs?

Cities near Renton, WA with the most Gpu Compiler Engineer job openings:

Infographic showing various Gpu Compiler Engineer job openings in Renton, WA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $93,688 per year, or $45 per hour.

Senior Performance Compiler Engineer - Triton

Seattle, WA • On-site

Nvidia
Computer and Electronic Product Manufacturing • 10K+ employees

$118K - $163K/yr

Full-time

Re-posted 20 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

NVIDIA's invention of the GPU 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, we are increasingly known as "the AI computing company".

We're looking for a Senior Performance Compiler Engineer to join our team and work on the open-source Triton compiler project. This opportunity involves working with new technologies and using compilers to improve AI performance on NVIDIA GPUs. Your work will enable breakthroughs in large language models, agents, and other high-impact AI applications, accelerating both training and inference. You will be immersed in a diverse, supportive environment where everyone is inspired to do their best work, pushing the limits of what's possible.

What you'll be doing:

  • Investigating the latest and future NVIDIA GPU hardware architecture and programming models.

  • Working on the frontier of AI by understanding advanced algorithms (like attention sinks and MoEs) and numerics (like block-scaled floating point) to identify new opportunities for optimization.

  • Designing and implementing compiler technology using MLIR to optimize high-level kernel descriptions (written in Triton's Python DSL), with a focus on generating efficient, low-level GPU code. When vital, you'll also be able to use inline PTX to hand-tune critical code paths and extract peak performance from the hardware.

  • Engaging in a dynamic, iterative process of optimization-sometimes starting with the kernel, sometimes with the compiler-to find the most efficient path to peak performance.

  • Collaborating with teams across NVIDIA, including hardware architects and the CUDA compiler team, to influence future products and ensure we are always operating at maximum efficiency.

What we need to see:

  • Bachelor, Masters or Ph.D. degree or equivalent experience in Computer Science, Computer Engineering, Applied Math, or a related field.

  • 8+ years of relevant industry experience in software development.

  • Demonstrated strong C++ programming and software design skills, with an emphasis on performance analysis and debugging.

  • Experienced in parallel programming, including CUDA/OpenCL GPU programming or other parallel models such as OpenMP.

  • Solid understanding of computer architecture and hands-on experience with assembly-level programming.

Ways to stand out from the crowd:

  • Experience in tuning BLAS or deep learning library kernels.

  • Background in numerics and linear algebra.

  • Experience with machine learning compilers like TVM or MLIR.

  • Contributions to open-source projects, especially in the AI/ML or compiler space.

  • Familiarity with the latest research in AI algorithms and numerics as well as a strong track record of contributions to open-source projects, particularly in the AI/ML, compiler, or high-performance computing domains.

With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 12, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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About Nvidia

Sourced by ZipRecruiter

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.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US