GPU Kernel Optimization Expert | CUDA/HIP | C++17 | Profiler-Guided Performance

Posted 2 weeks ago

Worldwide

Summary

We are seeking experienced GPU kernel optimization specialists to work on a cutting-edge AI project with a leading AI lab. RESPONSIBILITIES: - Analyze and optimize GPU kernels for performance, efficiency, and hardware utilization - Use profiler metrics (L2 cache hit rate, L2 throughput, occupancy) to guide kernel improvements - Write, modify, and reason about C++17, Python, and GPU programming code - Apply CUDA, HIP, or related kernel programming expertise to improve performance - Document optimization decisions clearly REQUIREMENTS: - Fluent in C++ through C++17 - Working knowledge of Python and Git - Fluent in at least one GPU programming model: CUDA, HIP, HLSL, GLSL, or similar - 1+ year professional or graduate-level GPU experience - Strong understanding of GPU profiler metrics (NSight Compute is a plus) - Available 20+ hrs/week NICE TO HAVE: - Experience with CUDA C++ Core Libraries, inline PTX assembly, or tensor core optimization - Experience optimizing kernels for NVIDIA Blackwell hardware - Open-source contributions related to GPU kernel optimization Rate: $80-100/hr | Remote | Contract

  • Less than 30 hrs/week
    Hourly
  • 3-6 months
    Duration
  • Expert
    Experience Level
  • $80.00

    -

    $100.00

    Hourly
  • Remote Job
  • Complex project
    Project Type
Skills and Expertise
Mandatory skills
Python
C++
CUDA
GPU
Performance Optimization
Activity on this job
  • Proposals:20 to 50
  • Interviewing:
    12
  • Invites sent:
    19
  • Unanswered invites:
    3
About the client
Member since Jun 19, 2026
  • Armenia
    11:15 PM

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