Remote GPU Kernel Optimization Engineer

mercor; United States; Remote; USD 568,000 - 809,000; Full time

Job summary

Mercor is seeking a CUDA Engineering Expert for a remote contract role focused on high-performance GPU kernel optimization. You will analyze kernels, leverage profiling metrics, and drive improvements across CUDA/HIP workflows.

Proficiency in C++17 and Python, plus experience with GPU profiling tools and NVIDIA/AMD ecosystem, will be essential for delivering performance gains remotely.

Qualifications

• Available to work at least 20 hrs/wk.
• Fluent in core C++ features through C++17.
• Working knowledge of Python and Git.
• Fluent in one GPU programming model like CUDA or HIP.
• 1+ year of GPU experience.
• Strong understanding of GPU profiler metrics.

Responsibilities

• Analyze and optimize GPU kernels for performance and hardware utilization.
• Use profiler metrics to guide kernel improvements.
• Review GPU kernel implementations and identify bottlenecks.
• Write and modify C++17, Python, and GPU programming code.
• Apply CUDA, HIP, and shader programming to improve performance.
• Document optimization decisions clearly with profiler metrics.

Skills

C++17

Python

Git

CUDA

HIP

GPU profiling

GPU kernels

Tools

CUDA Core Libs

NSight Compute

NVIDIA tools

Job description

Mercor is seeking a CUDA Engineering Expert for a remote contract role focused on high-performance GPU kernel optimization. You will analyze kernels, leverage profiling metrics, and drive improvements across CUDA/HIP workflows.

Proficiency in C++17 and Python, plus experience with GPU profiling tools and NVIDIA/AMD ecosystem, will be essential for delivering performance gains remotely.