CUDA Engineering Expert | $60-$100/hr Remote
Overview
A remote contract role focused on optimizing GPU kernels with CUDA for a customer project in collaboration with a top AI lab. You’ll profile, tune, and refactor CUDA and C++ code to boost throughput on modern GPUs. Experience with GLSL and WebGPU helps you implement shader logic and graphics workflows within existing pipelines. Clear, actionable documentation and technical communication are essential as you contribute to design discussions and stay current on GPU programming advances.
What You'll Do7
- 1Analyze and profile GPU kernels using CUDA and profiling tools to extract higher throughput on current hardware.
- 2Identify kernel bottlenecks with stakeholders and propose targeted optimization strategies.
- 3Refactor CUDA and C++ code to improve maintainability and adaptability across GPU architectures.
- 4Implement shader logic and graphics workflows with GLSL and WebGPU within existing pipelines.
- 5Document findings, steps taken, and performance gains in clear reports and technical notes.
- 6Contribute to design discussions on new GPU-based approaches and performance metrics.
- 7Keep up to date with GPU programming trends and share relevant insights to improve project outcomes.
Requirements6
- 1Proven CUDA programming experience with a track record of tuning GPU kernels for performance.
- 2Advanced C++ development skills in high-performance computing contexts.
- 3Hands-on experience with GLSL and WebGPU for graphics and compute shader work.
- 4Familiarity with GPU profilers (e.g., Nsight, Visual Profiler) for guided optimization.
- 5Strong analytical skills to assess kernel performance across different hardware generations.
- 6Excellent written and verbal communication for precise documentation and reporting.
Who Should Apply
The ideal candidate brings deep CUDA expertise and a history of practical kernel optimization. They should be comfortable collaborating with researchers and engineers in a remote, cross-disciplinary setup. This role may be less suitable for someone without hands-on GPU programming or who lacks experience with profiling tools. Common fit signals include a proven optimization track record and strong documentation habits; red flags are limited CUDA experience or difficulty translating profiling results into concrete improvements.
Salary Insight
Pay range is $60 - $100 per hour; compensation is discussed at the offer stage.
Location
Required Skills
Application Tip
Highlight a specific kernel you optimized, including before/after throughput and the profiling tools you used to measure the improvement.
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1Application received
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