CUDA Engineering Expert | Remote - Contract

Xperteez Technology,
Remote

About The Position

We are engaging CUDA Engineering Experts to contribute to a cutting-edge customer project focused on GPU kernel optimization in collaboration with a leading AI lab. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Requirements

  • CUDA
  • C++
  • GLSL
  • WebGPU

Nice To Haves

  • Demonstrated expertise in CUDA programming, with a strong track record of performance-tuning GPU kernels.
  • Advanced C++ development skills, particularly in high-performance computing environments.
  • Hands-on experience with GLSL and WebGPU for graphics and compute shader development.
  • Proficiency using GPU profilers (such as Nsight, Visual Profiler, or similar tools) for guided optimization.
  • Strong analytical abilities to evaluate and reason about kernel performance across hardware generations.
  • Excellent written and verbal communication skills—clear documentation and technical reporting are essential.
  • Experience collaborating in remote, cross-disciplinary project settings is a plus.

Responsibilities

  • Analyze, profile, and optimize GPU kernels using CUDA and relevant profiling tools to maximize computational throughput on modern hardware.
  • Collaborate with project stakeholders to assess and identify kernel bottlenecks, proposing targeted optimization strategies.
  • Refactor C++ and CUDA codebases for improved maintainability, efficiency, and adaptability across diverse GPU architectures.
  • Implement shader logic and graphics workflows using GLSL and WebGPU, ensuring seamless integration with existing pipelines.
  • Document key findings, optimization steps, and performance improvements with clear, actionable reports and technical communication.
  • Contribute expertise to design discussions, supporting the evaluation of new GPU-based approaches and performance metrics.
  • Stay informed on advancements in GPU programming and share relevant insights to enhance project outcomes.
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