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Gpu Kernel Developer Jobs (NOW HIRING)

Nvidia

Senior AI Software Engineer, Kernel Libraries

$125K - $165K/yr

As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for ... Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries ...

Nvidia

Senior AI Software Engineer, Kernel Libraries

$125K - $165K/yr

We're looking for outstanding AI systems engineers to develop groundbreaking technologies in the ... As a member of the team, you'll develop libraries, code generators, and GPU kernel technologies for ...

Anthropic

Performance Engineer, GPU

San Francisco, CA · On-site

$280K - $850K/yr

GPU Kernel Development: CUDA, Triton, CUTLASS, Flash Attention, tensor core optimization * ML ... Performance Engineering: Kernel fusion, memory bandwidth optimization, profiling with Nsight

Waymo

Software Engineer, GPU

Mountain View, NY · On-site

In this hybrid role, you will report to an Engineering Manager. You will: * Develop high ... Deep insights into GPU kernel performance, compilation flow, and driver stack * Knowledgeable of ...

YO AI Labs

CUDA Developer - Remote

Dallas, TX · Remote

$60 - $100/hr

Strong expertise in CUDA programming and GPU kernel optimization . * Advanced C++ development skills. * Hands-on experience with GLSL and WebGPU . * Experience using GPU profiling tools such as ...

YO AI Labs

CUDA Developer - Remote

Phoenix, AZ · Remote

$60 - $100/hr

Strong expertise in CUDA programming and GPU kernel optimization . * Advanced C++ development skills. * Hands-on experience with GLSL and WebGPU . * Experience using GPU profiling tools such as ...

YO AI Labs

CUDA Developer - Remote

Boston, MA · Remote

$60 - $100/hr

Strong expertise in CUDA programming and GPU kernel optimization . * Advanced C++ development skills. * Hands-on experience with GLSL and WebGPU . * Experience using GPU profiling tools such as ...

YO AI Labs

CUDA Developer - Remote

Seattle, WA · Remote

$60 - $100/hr

Strong expertise in CUDA programming and GPU kernel optimization . * Advanced C++ development skills. * Hands-on experience with GLSL and WebGPU . * Experience using GPU profiling tools such as ...

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How much do gpu kernel developer jobs pay per hour?

As of Sep 10, 2026, the average hourly pay for gpu kernel developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.

What is a GPU kernel developer?

A GPU Kernel Developer is a software engineer who specializes in writing and optimizing code (kernels) that runs on Graphics Processing Units (GPUs). These professionals use parallel programming languages such as CUDA or OpenCL to develop high-performance applications for tasks like scientific computing, deep learning, and graphics rendering. Their role involves designing algorithms that efficiently utilize GPU hardware to accelerate computations, debugging code, and collaborating with other engineers to integrate GPU-accelerated solutions into software systems.

What are the key skills and qualifications needed to thrive as a GPU kernel developer?

To thrive as a GPU Kernel Developer, you need strong programming skills in C/C++, parallel computing concepts, and a solid understanding of GPU architectures, often supported by a degree in computer science or related fields. Familiarity with CUDA or OpenCL, GPU profiling/debugging tools, and version control systems is typically required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills for this role. These skills are essential to efficiently develop, optimize, and maintain high-performance GPU code that meets the demands of modern computational workloads.

What are some common challenges faced by GPU kernel developers when optimizing code for different hardware architectures?

GPU Kernel Developers often encounter challenges when optimizing code for various hardware architectures due to differences in memory hierarchy, instruction sets, and parallel processing capabilities. Adapting kernels to utilize device-specific features while maintaining performance portability can be complex. Developers need to carefully manage resources such as shared memory and registers, and profile their code extensively to identify bottlenecks. Close collaboration with hardware engineers and regular benchmarking across devices are essential to achieve optimal results.

What are popular job titles related to Gpu Kernel Developer jobs?

For Gpu Kernel Developer jobs, the most frequently searched job titles are:

Infographic showing various Gpu Kernel Developer job openings in the United States as of September 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 100% In-person job distribution, with an average salary of $109,905 per year, or $52.8 per hour.

Senior Compute Kernel Architect, GPU Power

Santa Clara, CA • On-site

Nvidia Corporation
Computer and Electronic Product Manufacturing • 10K+ employees
Learn more about Nvidia Corporationexternal

Full-time

Re-posted 2 days ago

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 is seeking a Compute Kernel Performance Architect who can develop, profile, and analyze CUDA workloads with a strong focus on GPU power behavior. In this role, you will create specialized workloads that exercise the GPU's compute, memory, and I/O subsystems under demanding operating conditions. You will work closely with GPU architects, power architects, silicon validation engineers, and software teams to characterize workload behavior and influence the power architecture of future NVIDIA products. This position sits at the intersection of GPU architecture, high-performance software, and silicon characterization.
What You'll Be Doing:
  • Design and develop CUDA kernels and infrastructure that exercise worst-case power behavior across GPU compute, memory, and I/O subsystems.
  • Profile workloads to understand the relationship between kernel behavior, hardware utilization, performance, and power consumption.
  • Build workloads that generate controlled steady-state and transient power conditions across multiple GPU architectures.
  • Partner with GPU architects and silicon teams to identify functional units and workload patterns that require additional characterization.
  • Support power-stress methodology from pre-silicon modeling and simulation through post-silicon bring-up and validation.

What We Need to See:
  • MS or PhD or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field-or equivalent practical experience.
  • 5+ years of experience in CUDA programming, GPU kernel development, high-performance computing, or performance architecture.
  • Hands-on experience developing and optimizing GPU kernels, including work at the PTX or assembly level.
  • Experience with GPU performance-analysis tools such as Nsight Compute, Nsight Systems, nvprof, or equivalent tools.
  • Strong understanding of GPU build principles, including streaming multiprocessors, execution pipelines, memory hierarchy, synchronization, occupancy, and power states.
  • Excellent analytical, debugging, and communication skills.
  • Ability to work effectively across GPU architecture, software, silicon validation, and hardware engineering teams.

Ways to Stand Out from the Crowd:
  • Experience crafting GPU power-stress microbenchmarks or test-to-failure workloads.
  • Familiarity with Power Delivery Network concepts, including package and board-level behavior, impedance, inductance, decoupling, resonance, voltage droop, and overshoot.
  • Understanding of di/dt and how changes in current over time can compose voltage transients.
  • Experience with DVFS, AVFS, clock management, power states, or hardware noise-mitigation mechanisms.
  • Knowledge of how software workload patterns can interact with system-level power-delivery behavior.

Our team works at the core of NVIDIA's GPU performance and power stack. We collaborate closely with Compute Architecture, Power Architecture, Silicon Solutions, circuit-design teams, and deep-learning software teams. The workloads, tools, and analysis produced by this team help validate current products and influence the build of upcoming NVIDIA GPUs.
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 for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 26, 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

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