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Cuda Jobs in Bothell, WA (NOW HIRING)

Nvidia

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 as Parquet, ORC and JSON * Collaborate with distributed systems teams to craft solutions to ...

Nvidia

Backend Compiler Engineer

Redmond, WA

Experience in developing CUDA, DirectX, OpenGL/Vulkan applications NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and ...

General Robotics

Systems Engineer

Redmond, WA · On-site

$155K - $205K/yr

Optimize GPU/CUDA workloads and accelerate ML frameworks (PyTorch, JAX, TensorFlow) for robotics applications. * Build and maintain containerized deployment pipelines using Kubernetes and Docker.

Scale AI

ML Research Engineer, ML Systems

Seattle, WA · On-site

... such as CUDA, Pytorch, transformers, flash attention, etc. • Strong written and verbal communication skills and the ability to operate in a cross functional team environment Preferred : • ...

Nvidia

Senior GPU Compiler Development Engineer

Redmond, WA · On-site

$137K - $180K/yr

Work with NVIDIA GPU Architecture and CUDA Programming model teams to build abstractions to expose new GPU features in portable and performant ways in PTX ISA. PTX Compiler (PTXAS) apart from ...

Uw

Research Scientist/Engineer 1

Seattle, WA · On-site

$70K/yr

PyTorch/CUDA for segmentation/model inference. 3. Data stewardship: DVC or equivalent data versioning; basic dashboarding/monitoring (Prometheus/Grafana). 4. Domain breadth: Prior coursework/research ...

Adobe

Principal Machine Learning Engineer

Seattle, WA · On-site

Deep experience with inference frameworks and tools such asPyTorch, CUDA, Triton,TensorRT, Nvidia Dynamo, and Python. * Strong understanding of generative model architectures - diffusion models ...

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Cuda information

See Bothell, WA salary details

$124.6K

$230.3K

How much do cuda jobs pay per year?

As of Aug 19, 2026, the average yearly pay for cuda in Bothell, WA is $224,147.00, according to ZipRecruiter salary data. Most workers in this role earn between $229,200.00 and $229,200.00 per year, depending on experience, location, and employer.

What is a CUDA developer?

A CUDA job typically involves developing, optimizing, and implementing parallel computing applications using NVIDIA's CUDA platform. CUDA (Compute Unified Device Architecture) enables developers to leverage the power of GPUs for high-performance computing tasks such as deep learning, simulations, and scientific computing. Professionals in this role often work with C, C++, or Python, using CUDA libraries and frameworks to accelerate processing. Strong knowledge of parallel programming, memory management, and GPU architecture is essential for success in this field.

What are some common challenges faced when working as a CUDA developer, and how can they be addressed?

CUDA Developers often encounter challenges such as debugging complex parallel code, optimizing memory usage, and ensuring compatibility across different GPU architectures. To address these, it's important to leverage profiling tools like NVIDIA Nsight to identify bottlenecks and inefficiencies. Collaborating closely with team members, such as data scientists and software engineers, can also help in resolving integration issues and achieving better performance. Staying updated with the latest CUDA Toolkit releases and best practices is key to overcoming these challenges and delivering robust GPU-accelerated applications.

What are the key skills and qualifications needed to thrive as a CUDA developer, and why are they important?

To thrive as a CUDA Developer, you need strong programming skills in C/C++, a solid understanding of parallel computing concepts, and experience with GPU architectures. Familiarity with the CUDA toolkit, NVIDIA GPUs, and related profiling/debugging tools is typically required, and certifications in GPU programming can be advantageous. Analytical thinking, problem-solving, and effective communication are essential soft skills for optimizing code and collaborating with cross-functional teams. These skills are crucial for developing high-performance applications that leverage GPU acceleration, ensuring efficiency and innovation in compute-intensive fields.

What is the difference between Cuda vs GPU Developer?

AspectCudaGPU Developer
Required CredentialsKnowledge of CUDA programming, often with a background in computer science or engineeringExperience with GPU programming, CUDA, OpenCL, or similar; often requires a degree in computer science or related fields
Work EnvironmentPrimarily focused on developing and optimizing CUDA-based applications for NVIDIA GPUsDesigning, developing, and maintaining GPU-accelerated applications across various platforms and hardware
Industry UsageUsed mainly in high-performance computing, AI, and scientific research involving NVIDIA GPUsApplied across gaming, scientific computing, AI, and multimedia industries

In summary, CUDA is a specialized skill set focused on programming NVIDIA GPUs using CUDA, while a GPU Developer has a broader role that may include using various GPU programming tools and working across multiple platforms. CUDA is a subset of the skills a GPU Developer might possess, making them closely related but distinct roles.

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Cuda jobs near you
Infographic showing various Cuda job openings in Bothell, WA as of August 2026, with employment types broken down into 89% Full Time, 9% Part Time, and 2% Contract. Highlights an 77% Physical, 7% Hybrid, and 16% Remote job distribution, with an average salary of $224,147 per year, or $107.8 per hour.

Senior Software Engineer, CUTLASS Platform

Nvidia

Redmond, WA • On-site

$137K - $180K/yr

Full-time

Re-posted 19 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies

Job description

NVIDIA's high-performance computing platforms are powering the AI revolution across many applications and industries. Within our software stack, CUTLASS stands out as a popular open-source ecosystem dedicated to high-performance linear algebra and Tensor Core primitives. Since 2017, it has provided the community with C++ and Python abstractions to implement custom matrix multiply (GEMM) and related math and deep learning computations on NVIDIA GPUs.

If you are passionate about designing abstractions for Tensor Core and related GPU hardware features in MLIR, Python, and C++ that enable writing high performance kernels, apply to join the CUTLASS team today!

What you'll be doing:

  • Develop core components of the CUTLASS platform including Tensor Core MMAs, copies, synchronization barriers, schedulers, and other GPU hardware features in CUDA C++ and CUTLASS Python DSL.

  • Contribute to the advancement of the MLIR-based backend compiler stack for the CUTLASS Python DSL by designing dialects and associated compiler passes.

  • Author example kernels utilizing CUTLASS abstractions to showcase the use of novel GPU hardware features that are crucial for achieving high performance.

  • Collaborate with GPU architecture, CUDA, and NVVM/PTX compiler teams to provide feedback on programming models and to assess the performance of future GPU hardware features.

What we need to see:

  • Masters or PhD degree in Computer Science, Computer Engineering, or related field (or equivalent experience).

  • 3+ years of relevant industry experience.

  • Strong proficiency in C++ programming and software design, including debugging, performance evaluation, and testing.

  • Experience working with high-performance code generation and knowledge of compiler transformations and optimizations.

  • A deep understanding of computer architecture and parallel computing programming models.

Ways to stand out from the crowd:

  • Experience writing high-performance kernels at low levels of abstractions like NVVM/ PTX for GPUs or other similar parallel processing architectures.

  • Hands-on compiler design experience, particularly in MLIR.

  • Understanding of deep learning models, algorithms, and frameworks.

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard working people in the world working for us. If you're creative, autonomous, and love a challenge, consider joining our Deep Learning Library team and help us build the real-time, cost-effective computing platform driving our success in this exciting and quickly growing field.

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 June 5, 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.

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

Year founded

1993

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