GPU Kernel Performance Engineer (Contract)

Obsidian; San Francisco (CA); Remote; USD 83,000 - 138,000; Part time

Job summary

Mercor is seeking GPU kernel optimization experts to contribute to a project with a leading AI lab. This contract-based opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis.

You will evaluate, optimize, and reason about GPU kernels across modern hardware, writing and reviewing C++17, Python, and CUDA/HIP code.

Qualifications

• Experience with GPU kernel optimization and profiling to improve performance.
• Proficient in C++17 and Python programming.
• Experience with CUDA, HIP, or similar GPU programming models.

Responsibilities

• Analyze and optimize GPU kernels for performance and hardware utilization.
• Use profiler metrics (e.g., L2 cache, occupancy) to guide improvements.
• Write, modify, and reason about C++17, Python, and GPU code.
• Document optimization decisions clearly.

Skills

C++17

Python

GPU programming

Profiler metrics

Cuda/HIP

Tools

NSight Compute

Git

CUDA

HIP

Job description

Mercor is seeking GPU kernel optimization experts to contribute to a project with a leading AI lab. This contract-based opportunity is designed for freelancers with strong C++ skills, practical GPU programming experience, and the ability to improve kernel performance using profiler-guided analysis.

You will evaluate, optimize, and reason about GPU kernels across modern hardware, writing and reviewing C++17, Python, and CUDA/HIP code.