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Webgpu Developer Jobs in Santa Clara, CA (NOW HIRING)

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Develop shader logic using GLSL and WebGPU . * Document optimization processes, findings, and ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Develop shader logic using GLSL and WebGPU . * Document optimization processes, findings, and ...

GPU Programmer - Remote Job Type: Contractor Location: Remote Job Overview We are seeking ... Design, implement, and optimize GPU software using CUDA, WebGPU, or GLSL . * Profile and optimize ...

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Develop shader logic using GLSL and WebGPU . * Document optimization processes, findings, and ...

Design, build, and optimize GPU-based imaging and rendering features using modern C++, WebGPU, and ... Contribute to engineering docs and design reviews, and take part in regular code reviews About you ...

Senior Rendering Engine Software Engineer

Cupertino, CA · On-site

$151K - $199K/yr

We're looking for a Senior Rendering Engine Software Engineer who is excited by the challenge of ... 12, WebGPU) and shading languages (e.g., MSL, HLSL, GLSL, WGSL) Ability to use 3D geometry and ...

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How much do webgpu developer jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for webgpu developer in Santa Clara, CA is $62.06, according to ZipRecruiter salary data. Most workers in this role earn between $47.45 and $75.96 per hour, depending on experience, location, and employer.

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CUDA Developer - Remote

YO AI Labs

Palo Alto, CA • Remote

$60 - $100/hr

Full-time

Posted 16 days ago


Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities
  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications
  • 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 NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications
  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.