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NVIDIA

Designs the chips and software that power AI

Senior Solution Architect - AI Infrastructure

Implementation & Technical Account ManagementConfirmed live in the last 24 hours
Full-timeWashington, DC, USA

About the Job

Requirements

  • U.S. citizenship is required.
  • A BS, MS, or PhD in Electrical Engineering or Computer Science, or equivalent experience, is required.
  • At least 6 years supporting solution engineering or similar sales engineering or solution architecture, including direct work with partners and customers, is required.
  • Experience with high-performance networking or CPU/GPU application acceleration is required.
  • A background with schedulers such as SLURM, LSF, or UGE is required.
  • Experience with benchmarking tools such as HPL, NCCL tests, and MLPerf, as well as Kubernetes, is required.
  • Ability to travel to customer sites up to 20% of the time is required.

Responsibilities

  • Work with NVIDIA Cloud Partners and original equipment manufacturers in the public sector on large data center GPU server and networking system deployments.
  • Guide customer discussions on network design, compute and storage, and support server, network, and cluster deployments; visit customer data centers during bring-up.
  • Serve as the primary technical driver for customers during the build, deployment, construction, integration, and production of GPU infrastructure and applications throughout the customer lifecycle.
  • Conduct regular technical customer meetings covering product roadmaps, cluster issue debugging, feature discussions, and introductions to new technology solutions.
  • Partner with solutions architects, account managers, engineering, product, and business leaders to align strategies, assess technical needs, and secure business opportunities.
  • Analyze and debug compute and network configuration and performance issues to deliver performant clusters.
  • Prepare and deliver technical content to customers, including presentations, workshops, reference architectures, tutorials, and publications.
  • Lead communication with customers and NVIDIA management.
  • Provide constructive feedback to engineering and product teams regarding product requirements, customer experience, documentation, and tools.
  • Lead the resolution of technical issues across multiple engineering teams and coordinate solutions with the customer.

Desired Qualifications

  • Familiarity with NVIDIA GPUs, NVIDIA networking technologies such as network interface cards, RoCE, and InfiniBand, and systems technologies such as NCCL, DCGM, UFM, Mission Control, and Base Command Manager.
  • Experience building or integrating artificial intelligence solutions.
  • Experience bringing up and deploying large GPU clusters, including deploying and optimizing high-speed InfiniBand or Ethernet networks, and understanding how network architecture affects GPU cluster performance.
  • Experience with Message Passing Interface (MPI).
  • Experience working with enterprise developers and strong customer-facing skills.
  • An active security clearance is highly desirable.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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