Remote Infrastructure Support Engineer — GPU/AI Infra

Nscale; San Francisco (CA); On-site; USD 100,000 - 140,000; Full time

Benefits offered by this job

Equity

Remote-first

Flexible work

Annual salary reviews

Job summary

Nscale seeks an Infrastructure Support Engineer to maintain GPU fleets, handle tickets, and drive service reliability across data-centre operations, Linux, and data networks. You’ll own end-to-end tasks, triage hardware, interpret logs, and contribute to runbooks and automation with the team.

Ideal candidates have 3–4+ years in infrastructure support, strong GPU hardware troubleshooting, Bash/Python proficiency, and a growth mindset.

Qualifications

• 3+ years in infrastructure support or support engineering with customer-facing experience.
• Hands-on GPU infrastructure knowledge and hardware troubleshooting skills.
• Solid Linux CLI skills and basic scripting capabilities.
• Experience with ITSM processes, ticketing discipline, and clear documentation.
• Willingness to travel for deployments and training as needed.

Responsibilities

• Join support duty rotation and handle tickets and alerts with proper handovers.
• Perform GPU node triage, hardware troubleshooting, and log interpretation.
• Run diagnostics on fabric/links, capture evidence, and prepare vendor handovers.
• Assist with storage and data-path investigations on high-performance platforms.
• Document validated steps, contribute to runbooks, and share knowledge.
• Participate in on-call, learn Platform fundamentals, and travel when required.

Skills

GPU infrastructure

Linux

Networking

Ticketing/ITSM

Scripting basics

Platform/DC fundamentals

Growth mindset

Adaptability

Tools

nvidia-smi

NetBox

Bash

Python

Git

OpenStack

MAAS

Job description

Nscale seeks an Infrastructure Support Engineer to maintain GPU fleets, handle tickets, and drive service reliability across data-centre operations, Linux, and data networks. You’ll own end-to-end tasks, triage hardware, interpret logs, and contribute to runbooks and automation with the team.

Ideal candidates have 3–4+ years in infrastructure support, strong GPU hardware troubleshooting, Bash/Python proficiency, and a growth mindset.