CUDA Engineer Kernel Optimization

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco our investors include Benchmark General Catalyst Peter Thiel Adam DAngelo Larry Summers and Jack Dorsey.

Position: CUDA Engineering Expert
Type: Contract
Compensation: $500/hour
Location: Remote

Role Responsibilities

• Analyze and optimize GPU kernels for performance efficiency and hardware utilization.
• Use profiler metrics like L2 cache hit rate and occupancy to guide kernel improvements.
• Review GPU kernel implementations and identify bottlenecks without deep algorithmic background.
• Write and modify C17 Python and GPU programming code.
• Apply expertise in CUDA HIP and shader programming to improve performance.
• Document optimization decisions clearly focusing on profiler metrics utility.

Qualifications

Must-Have

• Available to work at least 20 hrs/wk.
• Fluent in core C features through C17.
• Working knowledge of Python and Git.
• Fluent in one GPU programming model like CUDA or HIP.
• 1 year of professional or research experience with GPUs.
• Strong understanding of GPU profiler performance metrics.

Preferred

• Experience with CUDA HIP and CUDA C Core Libraries.
• Experience optimizing kernels for NVIDIA Blackwell hardware.
• Familiarity with NSight Compute.
• Prior experience with NVIDIA AMD or Qualcomm.
• Open-source contributions related to GPU kernel optimization.

Application Process (Takes 2030 mins to complete)

• Submit your resume or relevant technical background.
• Qualified applicants may complete a brief technical assessment or submit additional information.

Resources & Support

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PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Employment Type : Full Time
Experience: years
Vacancy: 1