HPC/AI Infrastructure Engineer

HPC/AI Infrastructure Engineer

Overview

We are seeking a highly skilled HPC/AI Infrastructure Engineer to design, deploy, and manage advanced computing environments leveraging NVIDIA technologies, Kubernetes, and Linux systems. This role is critical to ensuring the performance, scalability, and reliability of AI workloads across GPU-accelerated clusters.

Key Responsibilities

• Deploy, configure, and manage NVIDIA Base Command Manager for orchestrating GPU workloads (critical).

• Implement and maintain NVIDIA AI Enterprise Suite to support enterprise-grade AI frameworks.

• Operate and optimize NVIDIA GPU and Network Operators within Kubernetes environments.

• Utilize NVIDIA NIMs and Blueprints to streamline AI model deployment and infrastructure automation.

• Administer and scale Slurm workload manager for HPC job scheduling (critical).

• Manage vanilla Kubernetes clusters, ensuring high availability and resource efficiency.

• Maintain and secure systems running on Canonical Ubuntu OS, including patching and performance tuning.

Required Skills & Qualifications

• Strong expertise with NVIDIA GPU technologies and AI infrastructure.

• Hands-on experience with Slurm in HPC environments.

• Proficiency in Kubernetes cluster administration.

• Deep knowledge of Linux (Ubuntu) system administration.

• Familiarity with network operators and GPU scheduling in containerized environments.

• Ability to troubleshoot complex distributed systems.

Preferred Skills

• Experience with automation tools (e.g., Ansible, Terraform).

• Knowledge of cloud-native architectures and hybrid HPC/AI deployments.

• Familiarity with observability tools (Prometheus, Grafana).

• Background in AI/ML workflows and performance optimization.

Work Environment

• Collaborative team working on cutting-edge AI and HPC solutions.

• Opportunity to shape infrastructure supporting enterprise-scale AI workloads.

• Exposure to NVIDIA’s latest ecosystem of AI and GPU technologies.