Energy HPC CUDA Performance Engineer

NVIDIA

United Arab Emirates

On-site

AED 420,000 - 660,000

Full time

13 days ago
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Job summary

NVIDIA is seeking a Compute Developer Technology (DevTech) expert to accelerate energy simulations and AI workflows. You will optimize CUDA performance on multi-GPU and multi-node systems and work with customer teams to deliver measurable speedups.

The role requires strong C/C++ and Python, CUDA programming, and experience with Nsight tools for profiling. You will engage with internal teams to influence roadmaps and build reusable libraries for future NVIDIA products.

Qualifications

  • BS/MS or equivalent in CS/CE/EE/Physics/Applied Math or related field.
  • Strong programming skills in C/C++ and Python on Linux.
  • Hands-on CUDA programming and GPU performance optimization experience.
  • Experience with profiling using NVIDIA Nsight Systems / Nsight Compute.

Responsibilities

  • Profile, analyze, and optimize GPU-accelerated applications focusing on CUDA kernels and memory movement.
  • Drive performance improvements across the stack, including MPI/NCCL multi-GPU/multi-node scaling.
  • Build reproducible benchmarks, performance reports, and tuning recommendations.
  • Develop reference implementations and patches to enable performance and portability.
  • Support customer engagements from POC to production and advise on deployment best practices.

Skills

C/C++
Python
CUDA programming
Profiling
MPI/NCCL
Linux
English
HPC optimization
Nsight tools

Education

BS/MS in CS/CE/EE/Physics/Applied Math

Tools

Nsight Systems
Nsight Compute

Job description

NVIDIA is seeking a Compute Developer Technology (DevTech) expert to accelerate energy simulations and AI workflows. You will optimize CUDA performance on multi-GPU and multi-node systems and work with customer teams to deliver measurable speedups.

The role requires strong C/C++ and Python, CUDA programming, and experience with Nsight tools for profiling. You will engage with internal teams to influence roadmaps and build reusable libraries for future NVIDIA products.

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