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CUDA Engineering ExpertRemoteJobsOne • Toronto, Canada
CUDA Engineering Expert

CUDA Engineering Expert

RemoteJobsOne • Toronto, Canada
1 day ago
Salary
CA$60.00–CA$100.00 hourly
Job type
  • Full-time
  • Remote
  • Quick Apply
Job description

This is a fully remote position, open to candidates based in Canada.

Pay: $60–$100/hr

Role Title: CUDA Engineering Expert

Role Type: Contractor

Location: Remote

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.

Scope of Work

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

Preferred Qualifications

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

How to apply

Apply here with your Indeed profile. We will then email you a link to complete your application on the hiring platform — your application is only considered once that final step is done.

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CUDA Engineering Expert • Toronto, Canada

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