NVIDIA
Artificial Intelligence
SeniorHPCArchitect,AutomationandAt-ScaleDeployment
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior HPC Architect, Automation and At-Scale Deployment at NVIDIA. Skills: HPC Architect, Automation, At-Scale Deployment, GPU Computing, Deep Learning. support deployment and bringup of large-scale GPU compute clusters. Provide insights on and implement at-scale system administration and tuning mechanisms for large-scale compute runs”
Industry & Context.
analytical skills
What They're Looking For.
Must Have
8+ years of experience using in accelerated computing for datacenter/HPC-based Enterprise computing solutions, Solid understanding of accelerated computing scheduling and I/O stacks, C/C++/Pythonash programming/scripting experience, Experience working with engineering or academic research community supporting high performance computing or deep learning, Experience with parallel filesystems, BS (or equivalent experience) in Engineering, Mathematics, Physics, or Computer Science
Nice to Have
MS or PhD desirable, Deep Learning framework skills, Exposure to using and deploying telemetry and visualization pipelines, Exposure to container technology and Linux performance tools
What You'll Do.
support deployment and bringup of large-scale GPU compute clusters
Provide insights on and implement at-scale system administration and tuning mechanisms for large-scale compute runs
work with the latest accelerated computing and Deep Learning software and hardware platforms
craft improved workflows and develop new
leading differentiated solutions
develop and bring up large scale performance platforms
Provide engineering solutions to operationalize the latest GPU Computing products and software stacks
ensure technical relationships with internal and external engineering teams
machine learning/deep learning engineers in building creative solutions based on NVIDIA technology
Be an internal reference for system administration
at-scale system analysis
and other datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community
How You'll Work.
Team & Collaboration
work with many scientific researchers, developers, and customers; interact with HPC, OS, GPU compute, and systems specialist; ensure technical relationships with internal and external engineering teams; assisting systems, machine learning/deep learning engineers
Communication Scope
communication skills, both verbal and written
Full Job Description
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice, join our diverse team today**!** We are looking for an outstanding hands-on architect/engineer for a Senior HPC architect role to support deployment and bringup of large-scale GPU compute clusters. Be a key player to enable the most exciting computing hardware and software and contribute to the latest breakthroughs in artificial intelligence and GPU computing. Provide insights on and implement at-scale system administration and tuning mechanisms for large-scale compute runs. You will work with the latest accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. **What you’ll be doing:** * Provide engineering solutions to operationalize the latest GPU Computing products and software stacks, ensure technical relationships with internal and external engineering teams, and assisting systems, machine learning/deep learning engineers in building creative solutions based on NVIDIA technology. * Be an internal reference for system administration, at-scale system analysis, and other datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community. **What we need to see:** * 8+ years of experience using in accelerate
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