AI, HPC & GPU Infrastructure Support Engineer
US$90,000 – US$150,000 / yr base salary
Posted 30 Jul 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$90,000 – US$150,000 / yr |
|---|
CertificationsRHCSA, CompTIA Linux+
About Us
Vast.ai's cloud powers AI projects and businesses all over the world. We are democratizing and decentralizing AI computing — reshaping our future for the benefit of humanity. Our mission is to organize, optimize, and orient the world's computation.
We value elegance, ownership, integrity, and continuous learning. You'll have the opportunity to dive into state-of-the-art AI systems while collaborating with a globally distributed team.
About the Role
This role focuses on troubleshooting complex Linux and GPU infrastructure issues across NVIDIA drivers, CUDA, GPU workloads, Ubuntu, Docker, KVM based virtual machines, networking, hardware, BIOS, and firmware. You’ll investigate failures, reproduce issues, identify root causes, and propose practical solutions across the full infrastructure stack.
You’ll also serve as the engineering resource our L1 support team relies on when tickets go beyond frontline triage. You’ll own complex escalations end-to-end, gather technical evidence, coordinate with the appropriate teams, and communicate findings clearly to clients, infrastructure suppliers, and internal teams.
The best engineers in this role don’t just resolve individual issues—they recognize recurring patterns, improve diagnostic tooling, and build runbooks that prevent future incidents. You’ll collaborate directly with the engineering and host support teams on systemic Linux, GPU, and infrastructure problems.
Strong GPU troubleshooting experience, Linux systems knowledge, and technical support skills are the primary requirements. You should be comfortable working autonomously in Ubuntu environments and troubleshooting NVIDIA drivers, CUDA, containers, virtual machines, networking, hardware, and GPU workloads.
Vast.ai users or hosts strongly preferred.
Location and Schedule
This is a full-time position based in our Westwood, Los Angeles office.
Available schedules:
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Monday–Friday: Fully on-site
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Sunday–Thursday: Four days on-site and one day working from home
Key Responsibilities
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Diagnose and resolve issues across NVIDIA CUDA/GPU drivers, Docker, and KVM virtualization environments
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Investigate GPU utilization, container resource constraints, thermal throttling, driver conflicts, and disk I/O bottlenecks