Senior HPC Architect, Automation and At-Scale Deployment

NVIDIA•Santa Clara, WA

65d

About The Position

NVIDIA is seeking an outstanding hands-on architect/engineer for a Senior HPC architect role to support the deployment and bring-up of large-scale GPU compute clusters. This role is crucial for enabling cutting-edge computing hardware and software and contributing to breakthroughs in artificial intelligence and GPU computing. The position involves providing insights and implementing 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, collaborating with scientific researchers, developers, and customers to refine workflows and develop new, differentiated solutions. Interaction with HPC, OS, GPU compute, and systems specialists is expected to architect, develop, and bring up large-scale performance platforms. The role includes providing engineering solutions to operationalize GPU Computing products and software stacks, maintaining technical relationships with internal and external engineering teams, and assisting systems, machine learning/deep learning engineers in building creative solutions based on NVIDIA technology. You will serve as an internal reference for system administration, at-scale system analysis, and other datacenter and large-scale GPU-accelerated system solutions within the NVIDIA technical community.

Requirements

8+ years of experience using accelerated computing for datacenter/HPC-based Enterprise computing solutions.
Solid understanding of accelerated computing scheduling and I/O stacks.
C/C++/Python/Bash programming/scripting experience.
Experience working with engineering or academic research community supporting high performance computing or deep learning.
Experience with parallel filesystems.
Strong teamwork and communication skills, both verbal and written.
Ability to multitask effectively in a dynamic environment.
Action driven with strong analytical skills.
Desire to be involved in multiple diverse and innovative projects.
BS (or equivalent experience) in Engineering, Mathematics, Physics, or Computer Science.

Nice To Haves

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.

Responsibilities

Provide engineering solutions to operationalize the latest GPU Computing products and software stacks.
Ensure technical relationships with internal and external engineering teams.
Assist 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.
Provide insights on and implement at-scale system administration and tuning mechanisms for large-scale compute runs.
Interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms.