NVIDIA

1 week ago

Solutions Architect – AI Factory

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Serve as a trusted technical advisor to help customers build AI Factory solutions using NVIDIA accelerated computing and deep learning platforms. Work in an interdisciplinary team to analyze customer AI training and inference cluster requirements, select suitable NVIDIA reference architectures, and coordinate implementation between NVIDIA deployment teams and customers. Provide hands-on post-deployment support to ensure Kubernetes-based training and inference workloads run effectively.

Location: Seoul

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Maintain up-to-date knowledge of NVIDIA reference architectures and their deployment methods for AI Factories.
•Analyze customer-initiated AI training or inference cluster requirements and map needs to the best reference architecture.
•Communicate the value proposition of selected NVIDIA reference architectures to collaborators.
•Coordinate seamless communication between NVIDIA internal deployment teams and customers during implementation.
•Provide hands-on technical support after AI Factory deployment to ensure workloads run effectively on the infrastructure.

Key Requirements

•Bachelor’s degree or higher in Computer Science, Computer Engineering, or a related technical field.
•5+ years of hands-on experience designing, deploying, and operating AI training or inference clusters using Kubernetes with NVIDIA GPUs.
•Experience with networking technologies such as InfiniBand and Ethernet in AI cluster environments, including compute fabric interconnects and management fabrics.
•Understanding of evolving NVIDIA Reference Architectures and their deployment methods.
•Proficiency with Kubernetes ecosystem technologies including CRI, CNI, Calico, NVIDIA GPU Operator, NVIDIA Network Operator, and Kubeflow Training Operator.

Experience:5+ yearsAIDeep learningHigh-performance computingKubernetes

Education:Bachelor's in Computer Science, Computer Engineering, or related technical field

Skills:CommunicationCollaborationCustomer advisorySelf-motivation

Tech Stack:NVIDIA DGX SuperPODNVIDIA Cloud Partner Reference DesignNVIDIA Enterprise Reference ArchitectureKubernetesNVIDIA GPUsContainer Runtime Interface (CRI)Container Network Interface (CNI)CalicoNVIDIA GPU OperatorNVIDIA Network OperatorKubeflow Training OperatorInfiniBandEthernet

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

1 week ago

Solutions Architect – AI Factory

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: Seoul

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Maintain up-to-date knowledge of NVIDIA reference architectures and their deployment methods for AI Factories.
•Analyze customer-initiated AI training or inference cluster requirements and map needs to the best reference architecture.
•Communicate the value proposition of selected NVIDIA reference architectures to collaborators.
•Coordinate seamless communication between NVIDIA internal deployment teams and customers during implementation.
•Provide hands-on technical support after AI Factory deployment to ensure workloads run effectively on the infrastructure.

Key Requirements

•Bachelor’s degree or higher in Computer Science, Computer Engineering, or a related technical field.
•5+ years of hands-on experience designing, deploying, and operating AI training or inference clusters using Kubernetes with NVIDIA GPUs.
•Experience with networking technologies such as InfiniBand and Ethernet in AI cluster environments, including compute fabric interconnects and management fabrics.
•Understanding of evolving NVIDIA Reference Architectures and their deployment methods.
•Proficiency with Kubernetes ecosystem technologies including CRI, CNI, Calico, NVIDIA GPU Operator, NVIDIA Network Operator, and Kubeflow Training Operator.

Experience:5+ yearsAIDeep learningHigh-performance computingKubernetes

Education:Bachelor's in Computer Science, Computer Engineering, or related technical field

Skills:CommunicationCollaborationCustomer advisorySelf-motivation

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor