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GPU Performance / Kernel Engineer

designworkstalentBellevueEngineering
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Salary
Not listed
Job type
Full-time
Work mode
Remote
Experience
Senior
Posted
7 Oct 2026
Status
Open · checked 7d ago

About this role

The GPU Performance / Kernel Engineer is a hybrid role based in Bellevue, Washington that suits engineers who enjoy deep technical challenges involving GPU computing, kernel optimization, and distributed AI workloads. This position focuses on tuning kernels, reducing latency, and maximizing throughput across large-scale training and inference environments.

Role Overview

The GPU Performance / Kernel Engineer position operates at the intersection of GPU architecture, AI workloads, systems performance, and low-level optimization. Open at Engineer, Senior, and Staff levels, the role requires working in a hybrid arrangement out of downtown Bellevue, involving approximately three days per week in the office. Candidates located elsewhere in the United States who are open to relocation may also apply.

Key Responsibilities

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.
Collaborate 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.

Requirements

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.
U.S. work authorization.

Nice to Have

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, high-performance computing environments, or cloud GPU infrastructure.
Familiarity with GPU profiling and optimization tools such as Nsight Systems, Nsight Compute, ROCm profiling tools, or similar technologies.

Skills and Tools

CUDA
ROCm
Nsight Systems
Nsight Compute
GPU compiler technologies
Distributed AI workloads
GPU architecture and memory hierarchy

Salary and Benefits

Competitive base pay for the Bellevue market.
Eligibility for additional rewards including merit increases, annual bonuses, and long-term incentives based on individual performance.
Medical, dental, and vision insurance for U.S.-based employees.
401(k) plan with company match.
Paid holidays per calendar year.

About the Company

designworkstalent represents a well-funded, rapidly growing AI infrastructure company building a next-generation cloud platform to power the full lifecycle of artificial intelligence. The organization combines the speed and innovation of a startup with the stability of an established parent organization, maintaining lean, collaborative, and AI-native engineering teams.

How to Apply

Interested candidates should apply on the official company careers page.

Skills and tech stack

CUDAROCmNsight SystemsNsight ComputeMachine LearningFine-tuning

Questions candidates ask

Where is the GPU Performance / Kernel Engineer role located?

The position is a hybrid role based in downtown Bellevue, Washington, requiring approximately three days per week in the office. Candidates across the U.S. who are open to relocation are also encouraged to apply.

Is visa sponsorship available for this position?

No, U.S. work authorization is required and visa sponsorship is not currently available.

What seniority levels are available for this job?

Multiple roles are available across Engineer, Senior, and Staff levels.

What benefits are provided for U.S.-based employees?

Employees receive medical, dental, and vision insurance, a 401(k) plan with company match, and paid holidays per calendar year.

What is the primary focus of the engineering work?

The role focuses on optimizing the data plane for large-scale AI workloads by improving GPU utilization, reducing latency, maximizing throughput, tuning kernels, and driving efficiency across the GPU fleet.

Ready to apply?

The application is on the official designworkstalent careers page.

Apply on company site