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Senior System Software Engineer - AI Performance and Efficiency Tools

NVIDIA· Engineer, Sys SW
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Shanghaifull-timePosted 4mo ago

About the role

Software engineering role focused on developing profiling, debugging, benchmarking, and simulation tools for AI workloads on GPU clusters. Collaborates with Architecture, Software, and HW teams to deliver insights, optimize performance and power efficiency, and debug complex issues.

Responsibilities

  • Build internal profiling and analysis tools for AI workloads at large scale
  • Build debugging tools for common encountered problems like memory or networking
  • Create benchmarking and simulation technologies for AI system or GPU cluster
  • Partner with HW architects to propose new features or improve existing features with real world use cases

Qualifications

  • BS+ in Computer Science or related (or equivalent experience) and 5+ years of software development
  • Strong software skills in design, coding (C++ and Python), analytical, and debugging
  • Good understanding of Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference
  • Knowledge of GPU cluster job scheduling (Slurm or Kubernetes), storage and networking
  • Experience with NVIDIA GPUs, CUDA Programming and NCCL
  • Motivated self-starter with strong problem-solving skills and customer-facing communication skills
  • Passion for continuous learning. Ability to work concurrently with multiple global groups

Skills

Required:C++PythonDeep Learning FrameworksGPU ClustersNVIDIA CUDADebuggingCommunicationContinuous Learning
Last updated Jul 3, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

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