NVIDIA
AI
SeniorDatacenterPerformanceModelEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Datacenter Performance Model Engineer at NVIDIA. Skills: performance modeling, AI workloads, GPU clusters, software development. Build performance modeling tools. Build prediction tools”
Industry & Context.
problem-solving skills; analytical
What They're Looking For.
Must Have
BS+ in Computer Science or related (or equivalent experience), 5+ years of software development, software skills in design, coding (C++ and Python), analytical, debugging, Deep Learning frameworks like PyTorch and TensorFlow, distributed training and inference, GPU cluster job scheduling (Slurm or Kubernetes), storage and networking, NVIDIA GPUs, CUDA Programming, Networking
Nice to Have
SW engineering experience experience in deploying SW at Dataceter scale, large AI job performance analysis for training/inference workload, Linux device drivers, compiler implementation, GPU architecture, CPU architecture, general computer architecture principles
What You'll Do.
Build performance modeling tools
Build prediction tools
Develop production tools
Search for configurations
Partner with architects
Improve existing features
How You'll Work.
Team & Collaboration
Partner with HW and SW architects; work concurrently with multiple global groups
Communication Scope
customer-facing communication skills
Full Job Description
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. We are looking for forward-thinking, hard-working, and creative people to join a fast-moving multifaceted software team! This software engineering role involves developing datacenter scale performance modeling and predictions tools for AI researchers running AI workloads in GPU clusters. **What you 'll be doing:** * Build performance modeling and prediction tools for AI workloads at Data-center scale * Develop production tools and workflows used by multiple teams both within NVIDIA and its customers. * Automate workflows including search for the most efficient configurations over millions of parameters * Partner with HW and SW architects to propose new features or improve existing features with real world use cases **What we need to see:** * 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 Networking * 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 **Ways to stand out from the crowd:** * Proven SW engineering experience experience in deploying SW at Dataceter scale * Solid experience in large AI job performance analysis for training/inference workload * Knowledge of Linux device drivers and/or compiler implementation * Knowledge of GPU and/or CPU architec
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