ContractRemoteExpired

CUDA Engineering Expert

micro1 is 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.

This job opportunity has expired.

The listing's valid-through date has passed. Its details remain available as a historical reference.

View Current Jobs

Salary

$60 - $100 / hour

Department

Engineering

Experience

Senior Level

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

CUDAC++GLSLWebGPUGPU ProgrammingGPU Kernel OptimizationHigh-Performance ComputingGPU ProfilingNsightCompute Shaders

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

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.

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.