AI Infrastructure Architect, MLOps & GPU HPC

NVIDIA Corporation; United States; Remote; USD 170,000 - 210,000; Full time

Job summary

NVIDIA Corporation is seeking an AI Factory Solution Architect to design and scale cutting-edge AI infrastructure across data centers, on-prem and cloud deployments. You will lead architectures that integrate NVIDIA GPUs and software stacks into HPC setups for scientific and engineering workloads, guiding multi-team initiatives.

The role requires deep expertise in distributed AI systems, on-prem Kubernetes, containerization, and modern DL frameworks such as PyTorch, vLLM, and TritonServer, with

Qualifications

• B.sc or M.sc in Engineering, Mathematics, Physics, or Computer Science or equivalent experience.
• 5+ years in software development or ML engineering.
• Experience with on-premises Kubernetes and containerization.
• Background with modern Deep Learning frameworks including PyTorch, vLLM and TritonServer.

Responsibilities

• Architect and scale high-performance, distributed AI infrastructure on-prem or in the cloud.
• Lead integration of NVIDIA technology into HPC architectures to support scientific and engineering applications.
• Be an internal champion for Deep Learning and Infrastructure among the NVIDIA technical community.
• Support Development activities and engage in POCs/POVs to validate new features and architectures.
• Develop solutions and showcase the AI ecosystem.

Skills

Software development

ML engineering

On-prem Kubernetes

Containers

MLOps tools

Education

B.Sc./M.Sc in Engineering/Math/Physics/CS

Tools

Kubernetes (K8S)

Docker

TritonServer

PyTorch

vLLM

Job description

NVIDIA Corporation is seeking an AI Factory Solution Architect to design and scale cutting-edge AI infrastructure across data centers, on-prem and cloud deployments. You will lead architectures that integrate NVIDIA GPUs and software stacks into HPC setups for scientific and engineering workloads, guiding multi-team initiatives.

The role requires deep expertise in distributed AI systems, on-prem Kubernetes, containerization, and modern DL frameworks such as PyTorch, vLLM, and TritonServer, with