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Senior Kernel Developer Jobs in Des Moines, WA (NOW HIRING)

... senior engineers. What You'll Do: * Optimize kernels for performance and resiliency across the ... Deliver critical kernel fixes and security mitigations with kernel live patches * Investigate and ...

Kernel Senior Software Engineer, Fuchsia

Seattle, WA · On-site

$139K - $183K/yr

As a Software Engineer on the Zircon Kernel team, you will design, implement, and maintain core operating system components including low-level context switching, thread scheduling, virtual memory ...

Sr. Mobile Engineer

Bellevue, WA · On-site

$150K - $188K/yr

Hi, We required Senior Mobile Engineer. These are direct hire permanent jobs with full benefits. If ... Should haveExperience with Linux kernel-space a plus * Should have Experience with networking ...

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Showing results 1-20

Senior Kernel Developer information

See Des Moines, WA salary details

$25.6K

$82.1K

$167.2K

How much do senior kernel developer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for senior kernel developer in Des Moines, WA is $82,081.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,400.00 and $105,300.00 per year, depending on experience, location, and employer.

What is the difference between Senior Kernel Developer vs Kernel Engineer?

AspectSenior Kernel DeveloperKernel Engineer
CredentialsBachelor's or higher in Computer Science, experience in kernel developmentSimilar credentials, often with specialized Linux or OS certifications
Work EnvironmentResearch and development, debugging, code optimizationDesign, implementation, testing of kernel modules and components
Industry UsageTech companies, hardware manufacturers, OS developersEmbedded systems, OS vendors, hardware integration

Both roles require strong knowledge of operating systems and kernel architecture. A Senior Kernel Developer typically focuses on advanced development and optimization, while a Kernel Engineer emphasizes designing and implementing kernel components. The roles often overlap but differ mainly in scope and focus within kernel development projects.

GPU Performance / Kernel Engineer

Designworks Talent

Bellevue, WA • Remote

Full-time

Medical, Dental, Vision, Retirement

Posted 29 days ago


Job description

GPU Performance / Kernel Engineer

Location: Hybrid | Bellevue, WA Area
Titles: Engineer, Senior and Staff (multiple roles available)

Optimize the Performance Layer Powering Next-Generation AI Infrastructure
About the Opportunity

A well-funded, rapidly growing AI infrastructure company is building a next-generation cloud platform designed to power the full lifecycle of artificial intelligence. The organization is developing a comprehensive AI infrastructure, platform, and services portfolio that supports the full spectrum of AI workloads—including large-scale compute, model training, fine-tuning, inference, and emerging agentic AI applications.

Backed by significant long-term investment, the company combines the speed, ownership, and innovation of a startup with the stability and resources of an established parent organization. Engineering teams are intentionally lean, highly collaborative, and AI-native, leveraging modern tooling and automation to build infrastructure capable of supporting the industry's most demanding AI workloads.

We're seeking GPU Performance / Kernel Engineers to optimize the data plane powering large-scale AI workloads. This role focuses on improving GPU utilization, reducing latency, and maximizing throughput across training and inference environments by tuning kernels, identifying performance bottlenecks, and driving efficiency across the GPU fleet.

 
 
The Opportunity

This is a high-impact engineering role focused on extracting maximum performance from large-scale GPU infrastructure. You'll work at the intersection of GPU architecture, AI workloads, systems performance, and low-level optimization.

As part of a highly technical infrastructure team, you'll analyze workload behavior, optimize performance-critical code paths, and develop the techniques and tooling required to operate AI systems efficiently at scale.

This opportunity is ideal for engineers who enjoy deep technical challenges involving GPU computing, kernel optimization, distributed AI workloads, and hardware/software performance.

 
 
What You'll Do
  • Profile, analyze, and optimize GPU kernels to improve latency, throughput, and overall utilization.

  • Identify and eliminate data-plane bottlenecks impacting GPU performance across large-scale AI workloads.

  • Tune performance-critical workloads across training and inference environments.

  • Work closely with AI infrastructure, machine learning, and platform engineering teams to understand workload characteristics and optimize system behavior.

  • Develop benchmarking methodologies and performance measurement practices across GPU infrastructure.

  • Evaluate emerging GPU technologies, performance tools, and optimization techniques as hardware platforms evolve.

  • Contribute to engineering practices that improve GPU efficiency, scalability, and reliability across the fleet.

 
What We're Looking For
  • Strong experience with GPU kernel development and performance optimization using technologies such as CUDA, ROCm, or comparable GPU programming frameworks.

  • Demonstrated experience improving GPU utilization, reducing latency, or increasing throughput for production AI workloads.

  • Strong understanding of GPU architecture, memory hierarchy, parallel computing, and the data path from application layer to hardware execution.

  • Experience profiling and debugging performance issues in complex AI or distributed computing environments.

  • Ability to independently own technically complex problems and drive solutions in a fast-moving engineering environment.

  • Strong systems programming and performance engineering mindset.

 
Preferred Qualifications
  • Experience optimizing workloads across multiple GPU platforms, including NVIDIA and AMD architectures.

  • Experience with GPU compiler technologies, runtime optimization, or low-level systems performance.

  • Contributions to open-source GPU performance projects, compiler tooling, or AI systems optimization.

  • Background working with large-scale AI training, inference platforms, HPC environments, or cloud GPU infrastructure.

  • Familiarity with GPU profiling and optimization tools such as Nsight Systems, Nsight Compute, ROCm profiling tools, or similar technologies.

 
Compensation
  • Competitive base pay for Bellevue market

  • Certain roles are eligible for additional rewards, including merit increases, annual bonus, and long term incentives. These awards are allocated based on individual performance

  • U.S. based employees have access to medical, dental, and vision insurance, a 401(k) plan and company match, employees also receive per calendar year, paid holidays.

 
Location
  • Hybrid role based in the Bellevue, WA area.

  • Approximately three days per week in the office.

  • Candidates elsewhere in the U.S. who are open to relocation are encouraged to apply.

  • U.S. work authorization is required. Visa sponsorship is not currently available.

 
Why Join?
  • Optimize the performance layer behind one of the industry's most advanced AI infrastructure platforms.

  • Work directly on GPU efficiency, kernel optimization, and large-scale AI workload performance.

  • Solve some of the hardest challenges in AI systems engineering—maximizing utilization, minimizing latency, and scaling compute efficiently.

  • Join early enough to influence architecture, tooling, and performance engineering practices.

  • Collaborate with world-class engineers building the infrastructure powering the next generation of AI applications.

  • Enjoy the technical ownership and impact of a startup environment backed by significant long-term investment.