Remote CUDA Engineering Expert

CUDA Engineering Expert$60 - $100/hourpay

Required Skills

CUDAC++GLSLWebGPU

About micro1

micro1 is the leading AI data lab for training frontier models and evaluating AI agents. Experts contribute their diverse subject matter knowledge across domains such as finance, healthcare, STEM engineering, and more. micro1 transforms that real-world expertise into high-quality training data, evaluations, and feedback loops that improve how AI systems learn, reason, and perform.

Our platform identifies and vets top talent through an AI recruiter, enabling high-quality expert contributions at scale. We aim to enable 1 billion people to do meaningful work by applying their expertise to AI. As our global expert network grows, micro1 is building the human intelligence layer for frontier AI.

Role Title: CUDA Engineering Expert

Role Type: Contractor

Location: Remote

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.

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.