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CUDA Engineer - Kernel Optimization - AI Trainer

Mercor

Job Description

Job Description

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 D'Angelo , 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 C++17 , 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 C++17 .
  • 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 20–30 mins to complete)

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

Resources & Support

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

#hiringmercor

Vacancy posted 6 days ago
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