CUDA GPU Optimization Engineer (Kernels & Shaders)

Crossing Hurdles; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Crossing Hurdles is seeking a GPU performance engineer to analyze, profile, and optimize CUDA kernels in high-performance C++ environments. You will collaborate with stakeholders to identify bottlenecks and propose optimization strategies, refactor code for multiple GPU architectures, and contribute shader logic using GLSL and WebGPU.

Documentation of findings and improvements will be a key deliverable. The role requires deep CUDA expertise, advanced C++ HPC skills, and hands-on shader

Qualifications

• Demonstrated expertise in CUDA programming with a strong track record in performance-tuning.
• Advanced C++ development skills in high-performance computing environments.
• Hands-on experience with GLSL and WebGPU for shader development.
• Proficiency using GPU profilers like Nsight or Visual Profiler for optimization.
• Strong analytical abilities to evaluate kernel performance across hardware generations.

Responsibilities

• Analyze, profile, and optimize GPU kernels using CUDA and relevant profiling tools.
• Collaborate with stakeholders to identify kernel bottlenecks and propose optimization strategies.
• Refactor C++ and CUDA codebases for improved efficiency across GPU architectures.
• Implement shader logic and graphics workflows using GLSL and WebGPU.
• Document findings, optimization steps, and performance improvements with clear reports.
• Contribute expertise to design discussions and evaluate new GPU-based approaches.

Skills

CUDA programming

C++ HPC

GLSL/WebGPU

GPU profiling

Kernel performance

Tools

Nsight

Visual Profiler

Job description

Crossing Hurdles is seeking a GPU performance engineer to analyze, profile, and optimize CUDA kernels in high-performance C++ environments. You will collaborate with stakeholders to identify bottlenecks and propose optimization strategies, refactor code for multiple GPU architectures, and contribute shader logic using GLSL and WebGPU.

Documentation of findings and improvements will be a key deliverable. The role requires deep CUDA expertise, advanced C++ HPC skills, and hands-on shader