GPU Infrastructure Engineer for AI & HPC

Vast.ai Inc.; Los Angeles, Northern (CA, KY); Hybrid; USD 90,000 - 160,000; Full time

Benefits offered by this job

Comprehensive health, dental, vision,

401(k) with company match

Meaningful equity

Onsite meals

Fast-paced startup culture

Job summary

Vast.ai is hiring for a full-time, on-site role in Westwood, Los Angeles to diagnose and resolve Linux and GPU infrastructure issues across NVIDIA drivers, CUDA, Docker and KVM. You’ll own escalations end-to-end, build runbooks, and collaborate with engineering and host support teams.

You’ll work autonomously in Ubuntu environments, automate with Python and Bash, and guide suppliers on hardware, BIOS, firmware, and network configuration to optimize performance.

Qualifications

• Strong Linux systems operations experience with Ubuntu, RHEL/CentOS, or Debian, including networking, storage, services, and permissions
• Proficiency with Docker, including container debugging, Docker Compose, image management, and storage/troubleshooting
• Experience with virtualization platforms such as Proxmox VE, VMware, or similar hypervisors, including VM provisioning and troubleshooting
• Strong networking fundamentals, including VLANs, DNS, DHCP, NAT, VPNs, firewall rules, and L2/L3 troubleshooting
• Hands-on experience with NVIDIA GPU drivers, CUDA, and GPU workload troubleshooting
• Python and Bash scripting for automation and diagnostics
• Strong written English communication that is clear, professional, and technically precise
• Experience providing technical support in a customer-facing or internal help desk environment
• Ability to prioritize across a concurrent queue of escalated tickets, triaging by severity and customer impact, balancing reactive resolution with proactive documentation and tooling

Responsibilities

• Diagnose and resolve issues across NVIDIA CUDA/GPU drivers, Docker, and KVM virtualization environments
• Investigate GPU utilization, container resource constraints, thermal throttling, driver conflicts, and disk I/O bottlenecks
• Assist clients and infrastructure suppliers working with TensorFlow, PyTorch, and other GPU-accelerated workloads
• Troubleshoot network-layer issues, including VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines
• Handle escalated support tickets involving GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration
• Provide managed support for supplier onboarding and ongoing machine management, including installation, configuration, and post setup troubleshooting
• Advise suppliers on hardware setup, driver configuration, BIOS and firmware settings, and network configuration for optimal performance
• Provide coverage for L1 support overflow during peak periods or incidents
• Write and maintain internal runbooks, escalation guides, and knowledge base articles to reduce repeat escalations
• Build diagnostic and automation tooling in Python and Bash to reduce manual triage overhead
• Collaborate with the engineering and support teams to flag and document systemic or recurring platform issues

Skills

Linux troubleshooting

NVIDIA drivers

Docker

KVM virtualization

Python scripting

Bash scripting

Networking basics

TensorFlow/PyTorch

GPU workloads

Customer support

Tools

Proxmox VE

VMware

Docker Compose

Job description

Vast.ai is hiring for a full-time, on-site role in Westwood, Los Angeles to diagnose and resolve Linux and GPU infrastructure issues across NVIDIA drivers, CUDA, Docker and KVM. You’ll own escalations end-to-end, build runbooks, and collaborate with engineering and host support teams.

You’ll work autonomously in Ubuntu environments, automate with Python and Bash, and guide suppliers on hardware, BIOS, firmware, and network configuration to optimize performance.