CUDA Engineering Expert

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.

Skills

Requirements

• 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, with clear documentation and technical reporting abilities.
• Experience collaborating in remote, cross-disciplinary project settings is a plus.

Benefits

• Remote contractor opportunity
• Contribute GPU and CUDA expertise to next-generation AI development
• Work on cutting-edge GPU kernel optimization projects
• Collaborate with stakeholders and leading AI technology teams
• Opportunity to influence AI system performance and GPU-based workflows