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Cuda Kernel Engineer Jobs in Texas (NOW HIRING)

Nvidia

Senior Software Engineer - TensorRT Edge-LLM

Austin, TX · Hybrid

$121K - $160K/yr

Contribute to CUDA kernel and operator development for critical transformer components such as ... Proficient programming ability with modern C++ (C++11/14/17 and beyond). * Familiarity with popular ...

Nvidia

Senior Software Engineer, CUTLASS Kernels

Austin, TX · On-site

$121K - $160K/yr

... CUDA library, and DL frameworks teams to ensure fast, functional, and timely kernel delivery to ... Strong proficiency in C++ programming and software design, including debugging, performance ...

General Motors

Staff ML Compiler Engineer

Austin, TX · On-site

We pioneernew approachesto model export,kernel development, and performance engineering so that ... GPU programming (CUDA) and familiarity with ML SW stack (e.g.,cuDNN,cuBLAS) * Experience with ML ...

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Cuda Kernel Engineer information

What are some 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.

What are Cuda Kernel Engineers?

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

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.
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Infographic showing various Cuda Kernel Engineer job openings in Texas as of July 2026, with employment types broken down into 100% Full Time. Highlights an 67% In-person, and 33% Remote job distribution.
Senior Systems Software Engineer, CUDA GPU Profiler

Senior Systems Software Engineer, CUDA GPU Profiler

NVIDIA

Austin, TX • On-site

$121K - $160K/yr

Full-time

Re-posted 29 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

Job Summary:
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. They are seeking a Senior Systems Software Engineer to develop innovative performance profiling tools for GPUs, collaborating with various teams to enhance GPU technology for future breakthroughs.
Responsibilities:
• Design and implement innovative features for our GPU performance profiling tools.
• Collaborate and interact with other teams within NVIDIA, including the GPU HW team, the compiler team, and well as other developer tools teams.
• Apply your own knowledge and skills to build tools that are instantly used by CUDA developers all over the world.
Qualifications:
Required:
• 8+ years proven experience in software engineering with a focus on performance tools.
• B.S. EE/CS (or equivalent experience).
• Strong programming skills in C++.
• Existing knowledge of GPU hardware and/or motivated to learn to closely collaborate with HW teams for design, bringup, and productization of new profiling features.
Preferred:
• Expertise in CUDA kernel programming and profiling.
• Outstanding interpersonal skills and the ability to collaborate effectively as part of a dynamic team.
• Highly motivated to apply your knowledge and eager to learn new skills in a fast-paced environment.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.

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Hours and flexibility

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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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