Technical Support Engineer
US$90,000 – US$130,000 / yr base salary
Posted 17 Jul 2026
Advertised as “Technical Support Engineer II (Linux)”
BranchFactor Summary
The original posting with the fluff stripped out
- Level
- II
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
| Base salary | US$90,000 – US$130,000 / 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 is a technical support role focused on escalated infrastructure issues that go beyond frontline triage. You'll be the engineering resource our L1 support team leans on when tickets get complex: diagnosing and resolving issues across the full stack — hardware/BIOS/firmware, networking, Ubuntu, Docker, NVIDIA CUDA/GPU, and virtualization (KVM).
You'll handle higher-complexity issues, own escalation resolution end-to-end, and contribute to internal documentation and runbooks. The best engineers in this role don't just resolve tickets — they build the tooling and runbooks that eliminate recurring ones. You'll collaborate directly with the engineering team and host support team on systemic issues.
Strong technical depth and support experience are the primary requirements. You should be comfortable working autonomously across Ubuntu environments, diagnosing container and GPU issues, and communicating findings clearly to both technical and non-technical audiences.
Vast.ai users or hosts strongly preferred.
This role is full-time and onsite in our office in Westwood (LA)
Schedule: Sunday - Thursday.
Key Responsibilities
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Handle escalated support tickets, including GPU workload failures, container issues, networking problems, account infrastructure, and host-side configuration
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Diagnose and resolve issues across Docker, NVIDIA CUDA/GPU drivers, and virtualization environments (KVM)
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Troubleshoot network-layer issues: VLAN, DNS, DHCP, VPN, NAT, firewall rules, and connectivity failures on host machines
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Investigate performance issues on GPU utilization, container resource constraints, thermal throttling, driver conflicts, disk I/O bottlenecks
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Advise suppliers (hosts) on installation best practices — hardware setup, driver configuration, BIOS/firmware settings, and network configuration for optimal performance