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Cuda Kernel Engineer Jobs in Kansas (NOW HIRING)

$105K - $138K/yr

We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the ... Strong experience in GPU kernel development and performance optimizations (especially using CUDA C ...

Cuda Kernel Engineer information

What is a CUDA Kernel Engineer?

Cuda Kernel Engineers are specialized software developers who design, implement, and optimize parallel computing algorithms using NVIDIA's CUDA platform. They write 'kernels,' which are functions that run on Graphics Processing Units (GPUs) to accelerate computational tasks in areas such as machine learning, scientific simulations, and graphics rendering. These engineers need strong skills in C/C++ programming, GPU architecture, and performance optimization techniques. Their work is crucial for applications that require high-speed data processing and efficient resource utilization.

What skills and qualifications are needed to be a CUDA Kernel Engineer?

To thrive as a CUDA Kernel Engineer, you need strong proficiency in C/C++ programming, parallel computing concepts, and a solid foundation in GPU architectures, typically supported by a degree in computer science or a related field. Expertise in NVIDIA CUDA toolkits, GPU profiling tools like Nsight, and familiarity with version control systems are essential. Analytical thinking, problem-solving abilities, and effective collaboration skills help engineers optimize code and work well within development teams. These skills and qualities are crucial for delivering high-performance, scalable GPU solutions in computationally intensive applications.

What are common challenges faced by CUDA Kernel Engineers when optimizing GPU code for performance?

Cuda Kernel Engineers often encounter challenges such as managing memory hierarchy efficiently, minimizing data transfer between host and device, and avoiding thread divergence. Ensuring optimal occupancy and maximizing parallelism while preventing bottlenecks like bank conflicts or uncoalesced memory access are also key concerns. Collaborating closely with software architects and data scientists is common, as solutions frequently require balancing algorithmic accuracy with hardware limitations. Addressing these challenges requires continuous profiling, testing, and iterative optimization.

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The top searched job categories for Cuda Kernel Engineer jobs in Kansas are:

Infographic showing various Cuda Kernel Engineer job openings in Kansas as of June 2026, with employment types broken down into 1% As Needed, 19% Full Time, 20% Part Time, 4% Temporary, 53% Contract, and 3% Nights. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution.

Senior Software Engineer, Matrix Multiplication

Nvidia

On-site

$105K - $138K/yr

Full-time

Posted 17 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

7th of 246 rated software companies


Job description

We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the inference systems software stack! We build innovative AI systems software to accelerate for AI inference. As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for NVIDIA's hardware architecture. This means designing and building things like new abstractions, efficient attention kernel implementations, new LLM inference runtimes components, and kernel code generators to accelerate large language models, agents, and other high-impact AI workloads.

What you'll be doing:

  • Innovating and developing new AI systems technologies for efficient inference

  • Designing, implementing, and optimizing kernels for high impact AI workloads

  • Designing and implementing extensible abstractions for LLM serving engines

  • Building efficient just-in-time domain specific compilers and runtimes

  • Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams

  • Contributing to open source communities like FlashInfer, vLLM, and SGLang

What we need to see:

  • Masters degree in Computer Science, Electrical Engineering, or related field (or equivalent experience); PhD are preferred

  • 6+ years (academic/ industry) experience with ML/DL systems development preferable

  • Strong experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc) and ideally inference engines and runtimes such as vLLM, SGLang, and MLC.

  • Strong Python and C/C++ programming skills

  • Strong experience in GPU kernel development and performance optimizations (especially using CUDA C/C++, cuTile, Triton, or similar) with hands-on experience with Matrix Multiplication

Ways to stand out from the crowd:

  • Background in domain specific compiler and library solutions for LLM inference and training (e.g. FlashInfer, Flash Attention)

  • Expertise in inference engines like vLLM and SGLang

  • Expertise in machine learning compilers (e.g. Apache TVM, MLIR)

  • Open source project ownership or contributions

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 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.

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