Senior AI Infrastructure Engineer

Job Title : Senior AI Infrastructure Engineer (NVIDIA GPU Systems / HPC Environment)

Location : Remote

Experience Required : 5+ years

Time Zone : PST

Position Overview :

We are seeking a highly experienced AI Infrastructure Engineer to support and optimize GPU-based server environments for AI/ML workloads and high-performance computing (HPC). The role involves 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 (192+ CPU cores, 2TB RAM, 8x NVIDIA GPU servers)

• Troubleshoot GPU infrastructure issues (hardware, CUDA, drivers, NVLink, PCIe)

• Support and optimize Mellanox InfiniBand networking for distributed compute operations

• Monitor and maintain AI/HPC clusters for ML training and inference

• Diagnose and resolve Linux system-level issues across GPU compute nodes

• Work with containerized/orchestration technologies (Docker, Kubernetes, Slurm, NVIDIA Container Toolkit)

• Support distributed AI workloads and GPU resource allocation

• Perform system tuning, patching, firmware updates, and performance optimization

• Collaborate with engineering teams to improve scalability and reliability

• Develop documentation, SOPs, and escalation procedures

Required Skills & Experience :

• 5+ years 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 GPU performance bottlenecks

• Familiarity with HPC or AI datacenter infrastructure

Preferred Qualifications :

• Experience with NVIDIA B200/B300, NVLink, RDMA, Slurm, OpenStack

• Experience with AI model training infrastructure

• NVIDIA certifications (preferred)

• RHCE or Kubernetes certifications (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

Please share candidate profiles that match these requirements along with their monthly costing at the earliest.