Senior System Software Engineer - AI Performance And Efficiency Tools

at Nvidia
📍 Santa Clara, United States
USD 184,000-356,500 per year
SENIOR
✅ Hybrid

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Software Development @ 6 Kubernetes @ 4 Linux @ 4 Python @ 7 TensorFlow @ 4 Communication @ 7 Networking @ 4 Debugging @ 4 PyTorch @ 4 CUDA @ 4 GPU @ 4

Details

A key part of NVIDIA's strength is our sophisticated analysis and debugging tools that empower NVIDIA engineers to improve performance and power efficiency of our products and the running applications. We are looking for forward-thinking, hard-working, and creative people to join a multifaceted software team with high standards! This software engineering role involves developing tools for AI researchers and software/hardware teams running AI workload in GPU clusters.

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 systems or GPU clusters
  • Partner with hardware architects to propose new features or improve existing features with real world use cases

Requirements

  • BS+ in Computer Science or related field (or equivalent experience) and 5+ years of software development
  • Strong 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 and ability to work concurrently with multiple global groups

Ways to Stand Out

  • Proven experience in GPU cluster scale continuous profiling & analysis tools/platforms
  • Solid experience in large AI job performance analysis for training/inference workloads
  • Knowledge of Linux device drivers and/or compiler implementation
  • Knowledge of GPU and/or CPU architecture and general computer architecture principles

Benefits

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.