NVIDIA

AI

SolutionsArchitect,OEMAIFactoryInfrastructure

$152–288k Santa Clara, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Solutions Architect, OEM AI Factory Infrastructure at NVIDIA. Skills: Solutions Architect, AI Factory Infrastructure, DevOps, HPC/AI workloads, Cluster Administration, Site Reliability Engineering, NVIDIA solutions. Contributing member of the OEM AI Factory SA team. Acquire insight into various facets of AI Factories deployments”

Industry & Context.

AI
Problems you'll solve

analytical and problem-solving skills

What They're Looking For.

Must Have

Linux system administration, Python, networking concepts, BS, MS, or PhD in Computer Science, Computer Architecture, Electrical Engineering, Math, Physics, Data Science, or related technical fields (or equivalent experience), 5+ years experience, skills in one or more programming languages (Python, C, C++, etc. ), Excellent presentation, communication and collaboration skills, Ability to work independently and with a cross-functional team, Comfortable multi-tasking in a fast-paced environment with changing requirements, analytical and problem-solving skills

Nice to Have

Solid understanding of Slurm, data sciences, NVIDIA GPUs and software libraries, Work experience within an engineering or research community, A computer architecture, software engineering, or data science foundation, Academic or industry familiarity with GPUs, AI, CUDA, or related technologies, data center infrastructure experience, from hardware up through technology stack

What You'll Do.

Contributing member of the OEM AI Factory SA team

Acquire insight into various facets of AI Factories deployments

Collaborating with solution architects

engineering or product teams

Understanding technical needs of partners and customers

Developing proof of concept projects with NVIDIA technologies

Assisting with key takeaways

documenting and sharing

Educating our Partners through hands-on trainings

How You'll Work.

Team & Collaboration

Collaborating with solution architects, engineering or product teams; Ability to work with a cross-functional team

Communication Scope

Excellent presentation, communication and collaboration skills

Full Job Description

In this role, you will be a contributing member of the OEM AI Factory SA team. Our work encompasses MEP (Mechanical Electrical Plumbing), Ethernet and Infiniband networking, DevOps, HPC/AI workloads, Cluster Administration and Site Reliability Engineering. You will acquire insight into various facets of AI Factories deployments. Applicants should be familiar with Linux system administration, Python, and networking concepts. Solid understanding of Slurm and data sciences is a plus. Our Team is responsible for OEM AI factory build engagements - which means that we work with our OEM partners (Dell, HPE, Lenovo and others) to use NVIDIA solutions integrated in their platforms. NVIDIA certified servers include GB200/300 NVL72, along with our software stack that assists with the deployment, configuring, validating and monitoring for the AI Factories of the future. **What you’ll be doing:** * Collaborating with solution architects, engineering or product teams! * Understanding technical needs of partners and customers * Developing proof of concept projects with NVIDIA technologies. * Assisting with key takeaways, documenting and sharing. * Educating our Partners through hands-on trainings. **What we need to see:** * BS, MS, or PhD in Computer Science, Computer Architecture, Electrical Engineering, Math, Physics, Data Science, or related technical fields (or equivalent experience) * 5+ years experience * Strong skills in one or more programming languages (Python, C, C++, etc.) * Excellent presentation, communication and collaboration skills * Ability to work independently and with a cross-functional team * Comfortable multi-tasking in a fast-paced environment with changing requirements * Strong analytical and problem-solving skills **Ways to stand out from the crowd:** * Experience with NVIDIA GPUs and software libraries * Work experience within an engineering or research community * A computer architecture, software engineering, or data science foundation * Academic or ind

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