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Cuda Engineer Salary Jobs in Bothell, WA (NOW HIRING)

Experience with CUDA kernels, NCCL/SHARP, RDMA/NUMA, or GPU interconnect topologies. * Leading ... The starting salary will be determined based on job-related knowledge, skills, experience, and ...

Senior System Software Engineer

Redmond, WA · On-site

$137K - $180K/yr

Enable C++ native execution of Spark operations on CUDA Develop CUDA/C++ libraries to accelerate ... base salary will be determined based on your location, experience, and the pay of employees in ...

Senior System Software Engineer

Redmond, WA · On-site

$137K - $180K/yr

Develop CUDA/C++ libraries to accelerate DataFrames and I/O operations on common file formats such ... The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for ...

Showing results 41-60

Cuda Engineer Salary information

See Bothell, WA salary details

$40.8K

$119.9K

$153.7K

How much do cuda engineer salary jobs pay per year?

As of Sep 4, 2026, the average yearly pay for cuda engineer salary in Bothell, WA is $119,929.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,900.00 and $152,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a CUDA engineer?

To thrive as a CUDA Engineer, you need strong programming expertise in C/C++, parallel computing concepts, and a solid understanding of GPU architecture, typically supported by a degree in computer science or a related field. Experience with NVIDIA CUDA toolkit, GPU profiling tools, and parallel computing frameworks is essential, and certifications in CUDA development can be advantageous. Analytical thinking, problem-solving abilities, and effective communication skills help distinguish top performers in this field. These skills and qualities are crucial for developing efficient, high-performance applications and collaborating on complex technical projects.

What is the average salary of a CUDA engineer?

The average salary of a CUDA Engineer in the United States typically ranges from $110,000 to $160,000 per year, depending on experience, location, and industry. CUDA Engineers with specialized skills in GPU programming and parallel computing are often in high demand, particularly in sectors such as artificial intelligence, high-performance computing, and graphics. Salaries may be higher in tech hubs like Silicon Valley or for engineers with advanced degrees and significant experience.

What are some common challenges faced by CUDA engineers when collaborating with cross-functional teams?

CUDA engineers often work closely with software developers, data scientists, and hardware engineers to optimize code for GPU acceleration. A common challenge is effectively communicating complex GPU programming concepts to team members who may not have a background in parallel computing. Additionally, integrating CUDA code into broader projects can require careful coordination to ensure compatibility and performance across different platforms. Overcoming these challenges often involves clear documentation, regular team meetings, and a willingness to provide technical guidance to colleagues.

What is the difference between Cuda Engineer Salary vs GPU Developer Salary?

AspectCuda Engineer SalaryGPU Developer Salary
Required CredentialsBachelor's or higher in Computer Science, Engineering, or related fields; knowledge of CUDA, parallel programmingBachelor's or higher in Computer Science, Software Engineering, or related fields; experience with GPU programming
Work EnvironmentResearch labs, tech companies, AI firms, hardware manufacturersSoftware development companies, gaming industry, AI and machine learning firms
Industry UsagePrimarily in high-performance computing, AI, and scientific researchIn gaming, visualization, AI, and software optimization

Both roles require expertise in GPU programming and similar educational backgrounds. Cuda Engineers focus more on developing and optimizing CUDA-based applications, while GPU Developers work broadly on GPU-accelerated software. Salary differences depend on experience, location, and industry demand, but both roles are highly valued in tech sectors leveraging GPU technology.

Are CUDA engineers in demand?

CUDA engineers are in high demand due to the growing use of GPU computing in fields like artificial intelligence, machine learning, and high-performance computing. Skills in CUDA programming, parallel processing, and related tools are highly valued by employers across technology, research, and industry sectors.

What does a CUDA engineer do?

A CUDA engineer develops software that leverages NVIDIA's CUDA platform to perform parallel processing on GPUs, optimizing high-performance computing tasks such as scientific simulations, machine learning, and graphics rendering. They typically have skills in C/C++, GPU architecture, and debugging tools, working in environments that require efficient parallel code development.

What job categories do people searching Cuda Engineer Salary jobs in Bothell, WA look for?

The top searched job categories for Cuda Engineer Salary jobs in Bothell, WA are:

What cities near Bothell, WA are hiring for Cuda Engineer Salary jobs?

Cities near Bothell, WA with the most Cuda Engineer Salary job openings:

Senior Deep Learning Compiler Engineer - XLA

Nvidia

Redmond, WA

$117K - $160K/yr

Full-time

Re-posted 10 days ago


Key responsibilities

  • Develop compiler optimization algorithms for deep learning workloads.

  • Optimize inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs.

  • Collaborate with deep learning framework teams and hardware architecture teams to accelerate deep learning software.


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


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 are looking for versatile software engineers for our XLA team. NVIDIA is at the center for the AI revolution that's transforming how people live, work, and interact with technology. Come join us to build high-performance, production-grade software that's at the core of next-generation AI systems.

What you will be doing: In this role, develop compiler optimization algorithms for deep learning workloads. You will optimize inference and training performance for the JAX framework and the OpenXLA compiler on NVIDIA GPUs at scale. You'll collaborate with our partners in deep learning framework teams and our hardware architecture teams to accelerate the next generation of deep learning software.

The scope of these efforts include: Crafting and implementing compiler optimization techniques for deep learning network graphs. Designing novel graph partitioning and tensor sharding techniques for distributed training and inference. Performance tuning and analysis.

Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton. Designing user facing features in JAX and related libraries and other general software engineering work. Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.

What we need to see: Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience). 4+ years of relevant work or research experience in performance analysis and compiler optimizations

Ability to work independently, define project goals and scope, and lead your own development effort adopting clean software engineering and testing practices. Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design. Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators.

Knowledge of high-performance computing and distributed programming. CUDA or OpenCL programming experience is desired but not required. Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.

Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. A history of mentoring junior engineers and interns is a bonus. Ways to stand out from the crowd: Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow.

Extensive experience with CUDA or with GPUs in general. Experience with open-source compilers such as XLA, LLVM, MLIR or TVM. 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until August 18, 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. #deeplearning


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


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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