Sr AI Infrastructure Engineer

Kindly find below the for the post of Senior AI Infrastructure Engineer.

Location: Remote

Shift: US Shift/ Night Shift

Position Overview

We are seeking a highly experienced AI Infrastructure Engineer to support and optimize advanced GPU-based server environments designed for AI/ML workloads and high-performance computing (HPC). The ideal candidate will possess deep expertise in NVIDIA GPU infrastructure, Linux systems, distributed compute environments, Mellanox InfiniBand networking, and AI cluster operations. This role involves Level 3 (L3) support, troubleshooting, optimization, and maintenance of enterprise AI compute environments containing high-density GPU servers.

Key Responsibilities

• Manage and support high-performance AI server infrastructure with:
• 192+ CPU cores
• 2TB RAM configurations
• 8x NVIDIA GPU server environments
• Troubleshoot complex GPU infrastructure issues involving:
• NVIDIA GPU hardware
• CUDA environments
• GPU drivers and firmware
• NVLink and GPU fabric architecture
• PCIe performance issues
• Support and optimize Mellanox InfiniBand networking environments for low-latency AI workloads and distributed compute operations.
• Monitor and maintain AI/HPC clusters used for machine learning training and inference workloads.
• Diagnose and resolve Linux system-level issues across GPU compute nodes.
• Work with containerized and orchestration technologies such as:
• Docker
• Kubernetes
• Slurm
• NVIDIA Container Toolkit
• Support distributed AI workloads and GPU resource allocation across multiple systems.
• Perform system tuning, patching, firmware updates, and performance optimization.
• Collaborate with internal engineering teams to improve infrastructure scalability, reliability, and uptime.
• Develop documentation, SOPs, and escalation procedures for infrastructure operations.

Required Skills & Experience

• 5+ years of experience supporting Linux-based enterprise infrastructure
• Strong experience with NVIDIA GPU systems in AI/HPC environments
• Hands-on experience with CUDA and GPU driver management
• Experience supporting GPU clusters or AI training infrastructure
• Knowledge of Mellanox InfiniBand networking
• Strong understanding of distributed compute environments
• Experience with Docker and Kubernetes
• Experience troubleshooting performance bottlenecks in GPU environments
• Familiarity with HPC or AI datacenter infrastructure

Preferred Qualifications

• Experience with: NVIDIA B200/B300, NVLink, RDMA, Slurm workload manager, OpenStack, AI model training infrastructure
• NVIDIA certifications preferred
• RHCE or Kubernetes certifications are a plus

Soft Skills

• Strong analytical and troubleshooting abilities
• Ability to work independently in complex technical environments
• Excellent communication and documentation skills
• Comfortable working in fast-paced AI infrastructure environments

• Support Level
• Level 3 (L3) Infrastructure Support
• Environment
• AI Infrastructure / HPC / GPU Datacenter Operations