GPU Performance, Kernel Engineer

Designworks Talent LLC

GPU Performance Engineer optimizing performance across GPU infrastructure for AI workloads. Focus on kernel optimization and throughput maximization in a hybrid role based in Bellevue, WA.

Posted 7/29/2026full-timeBellevue • Washington • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in GPU kernel development and performance optimization, with a strong focus on improving latency, throughput, and overall utilization in large-scale AI workloads. Proficient in profiling, debugging, and optimizing GPU performance across various architectures and environments.

Highest-signal resume keywords

GPU Kernel DevelopmentPerformance OptimizationCUDA ProgrammingGPU Architecture UnderstandingAI Workload Optimization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GPU Kernel DevelopmentPerformance OptimizationCUDAROCmParallel ComputingSystems ProgrammingPerformance EngineeringGPU Compiler TechnologiesDebugging Performance IssuesAI Systems Optimization

Soft Skills

Problem SolvingIndependent Ownership

Tools & Technologies

Nsight SystemsNsight ComputeROCm Profiling ToolsBenchmarking MethodologiesPerformance Measurement Practices

Industry Keywords

AI WorkloadsHPC EnvironmentsCloud GPU InfrastructureLarge-Scale AI TrainingInference Platforms

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.
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.

Benefits

Comp & perks

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.