AI Infrastructure Architect

The Adecco Group

0 years

0 Lacs

chennai tamil nadu india

Posted:1 week ago| Platform:

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Skills Required

ai design ml server support architecture deployment training networking strategies model inference software integration data containerization orchestration monitoring logging optimization procurement storage leadership security compliance drive automation provisioning configuration management code planning technology

Work Mode

On-site

Job Type

Full Time

Job Description

Design and implement large-scale AI/ML infrastructure solutions using NVIDIA GPU clusters, SMCI server platforms, and high-performance computing architectures to support enterprise AI workloads
Lead the architecture and deployment of distributed AI training environments, including multi-node GPU clusters, InfiniBand networking, and parallel computing frameworks like NVIDIA NVLink and NVSwitch
Develop comprehensive infrastructure strategies for AI model training, inference, and deployment across on-premises, cloud, and hybrid environments using SMCI hardware solutions and NVIDIA AI Enterprise software stack
Oversee the integration of AI accelerators, including NVIDIA A100, H200, and emerging GPU architectures, with SMCI SuperServer platforms to optimize performance and resource utilization
Collaborate with data science teams to design scalable MLOps pipelines, model serving infrastructure, and automated deployment systems using containerization and orchestration technologies
Establish monitoring, logging, and performance optimization frameworks for AI workloads, implementing solutions like NVIDIA Triton Inference Server and GPU monitoring tools
Lead technical due diligence for AI hardware procurement decisions, including SMCI server configurations, NVIDIA GPU selections, and storage solutions for large-scale AI datasets
Mentor junior infrastructure engineers and provide technical leadership in AI infrastructure best practices, including security, compliance, and cost optimization strategies
Drive automation initiatives for AI infrastructure provisioning, configuration management, and lifecycle management using Infrastructure as Code principles
Partner with stakeholders to define AI infrastructure roadmaps, capacity planning, and technology adoption strategies aligned with business objectives

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