Role at a glance
- Salary
- Not Disclosed
- Location
- 당산SK V1 center W1209호), Seoul, South Korea
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 7+ years
- Education
- Bachelor's
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Qualifications
Required
- Bachelor's degree or higher in Computer Science, Computer Engineering, or a related technical field.
- Minimum of 7 years of hands-on experience designing, deploying, and operating AI training or inference clusters with server, storage, and network, that leverage Kubernetes with NVIDIA GPUs.
- Foundational knowledge and experience with networking technologies—such as InfiniBand and Ethernet—in AI cluster environments, including compute fabric interconnects between GPU servers, storage fabric integration, and out-of-band and...
Preferred
- Proficiency in key technologies including: Container Runtime Interface (CRI), Container Network Interface (CNI), Calico, NVIDIA GPU Operator, NVIDIA Network Operator, and Kubeflow Training Operator.
- Knowledge and experience of facilities being used in building AI Factories, including cooling devices, power distribution, or plumbing.
About the role
Original posting provided by 엔비디아(NVIDIA)
About the role
NVIDIA is seeking an outstanding Solutions Architect for AI Factory to assist and support customers that are building solutions with our newest AI technology. At NVIDIA, our Solutions Architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning software and hardware platforms. You will become a trusted technical advisor with our customers and work on exciting projects and proof-of-concepts passionate about AI Factory.
What you'll do
• Maintain an up-to-date understanding of the philosophy, architecture, and deployment methods of various evolving NVIDIA Reference Architectures—e.g., NVIDIA DGX SuperPOD Reference Architecture, NVIDIA Cloud Partner Reference Design, and NVIDIA Enterprise Reference Architecture.
• Analyze and understand the requirements of customer-initiated AI training or inference clusters.
• Identify the NVIDIA Reference Architecture that best matches customer needs and effectively communicate its value proposition to collaborators.
• Facilitate seamless communication between NVIDIA's internal deployment teams and customers during the implementation of AI clusters based on Reference Architectures.
• Provide hands-on technical support to developers after the AI Factory has been deployed, ensuring that AI training and inference workloads run effectively on the infrastructure.
Requirements
• Bachelor's degree or higher in Computer Science, Computer Engineering, or a related technical field.
• Minimum of 7 years of hands-on experience designing, deploying, and operating AI training or inference clusters with server, storage, and network, that leverage Kubernetes with NVIDIA GPUs.
• Foundational knowledge and experience with networking technologies—such as InfiniBand and Ethernet—in AI cluster environments, including compute fabric interconnects between GPU servers, storage fabric integration, and out-of-band and in-band management fabrics.
Preferred qualifications
• Proficiency in key technologies including: Container Runtime Interface (CRI), Container Network Interface (CNI), Calico, NVIDIA GPU Operator, NVIDIA Network Operator, and Kubeflow Training Operator.
• Knowledge and experience of facilities being used in building AI Factories, including cooling devices, power distribution, or plumbing.
Benefits
자세한 사항은 홈페이지 참조
About the company
엔비디아(NVIDIA)
고성능 GPU와 병렬 컴퓨팅 아키텍처를 기반으로 인공지능 연산과 그래픽 가속화를 이끄는 글로벌 반도체 기술 기업입니다. 딥러닝과 데이터 센터, 자율주행 기술의 연산 인프라를 독점적으로 제공하며 인공지능 시대의 핵심 동력이 되는 기술 표준을 정립해 나가고 있습니다.