Staff GPU Infrastructure

Job Summary

We are seeking a Staff GPU Infrastructure / Bare-Metal Platform Engineer to design, deploy, automate and maintain large-scale GPU computing infrastructure supporting AI/ML workloads.

Responsibilities

• Design, deploy, automate and maintain large-scale bare-metal GPU server infrastructure.
• Develop infrastructure automation tools to accelerate GPU server provisioning, deployment and operational readiness.
• Configure and maintain Linux-based GPU servers and operating systems.
• Implement automated bare-metal provisioning using PXE boot, MAAS or equivalent technologies.
• Deploy, configure, administer and troubleshoot Kubernetes clusters supporting AI/ML workloads.
• Manage GPU server hardware, BMC/IPMI, BIOS, firmware, operating systems and driver configurations.
• Diagnose GPU hardware failures, server-level issues, provisioning failures and infrastructure performance problems.
• Coordinate hardware troubleshooting, replacement and maintenance with enterprise server vendors.
• Develop infrastructure automation and operational software using Golang or Python.
• Implement infrastructure as code and configuration management using Ansible and Terraform.
• Develop monitoring, health-checking, alerting and automated recovery capabilities.
• Support infrastructure capacity planning, reliability, scalability and performance improvements.
• Collaborate with GPU platform, networking, storage, security and data center operations teams.
• Support the transition toward Kubernetes-based and containerized infrastructure.
• Maintain technical documentation, troubleshooting procedures and operational runbooks.

Required Experience & Skills

• 8+ years of experience in infrastructure engineering, systems engineering, platform engineering, DevOps, SRE, or related roles.
• Advanced hands-on Linux systems administration and troubleshooting.
• Strong experience with bare-metal server provisioning and automated OS deployment.
• Hands-on experience deploying, administering and troubleshooting Kubernetes clusters.
• Strong programming experience with Python or Golang, preferably Golang.
• Experience with infrastructure automation using Ansible and Terraform.
• Strong understanding of BMC/IPMI, BIOS, firmware and enterprise server management.
• Experience troubleshooting physical server hardware, preferably GPU-based systems.
• Experience supporting large-scale infrastructure environments.
• Strong understanding of server lifecycle management, infrastructure reliability and operational automation.
• Experience with NVIDIA DGX, HGX, or equivalent GPU server infrastructure.
• Experience with Canonical MAAS.
• Familiarity with NVIDIA GPU drivers, CUDA environments and NVIDIA DCGM.
• Experience with Docker and containerization technologies.
• Experience with Prometheus, Grafana, or equivalent infrastructure monitoring tools.
• Familiarity with Slurm, NVIDIA Run AI, or other GPU workload orchestration platforms.
• Experience supporting distributed AI training infrastructure.
• Experience with high-performance networking, InfiniBand, or RoCE.
• Experience with AI cloud platforms and hyperscale infrastructure.