Manage and sustain a large fleet of GPU servers, including H100, B200, and GB200 models, used for AI and machine learning applications, ensuring optimal performance, system health, and adherence to service level agreements
Diagnose and resolve intricate issues involving hardware, firmware, operating systems, and applications within GPU clusters, collaborating with vendors and engineering teams to address recurring problems
Create and maintain automated scripts to enable scalable server provisioning, configuration, monitoring, and issue remediation
Design and enhance tools for GPU health monitoring, performance analysis, driver verification, and self-healing recovery processes
Carry out server setup, OS installation, firmware upgrades, and configuration using automated platforms, overseeing full lifecycle operations from deployment to retirement
Join a round-the-clock on-call schedule to respond to critical system incidents and work with infrastructure, networking, and software teams to restore services
Lead incident post-mortems, identify root causes, and implement improvements to boost automation, system reliability, monitoring, and operational effectiveness

Competitive total compensation package including salary and equity

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Participation in a 24x7 on-call rotation is required
The annual base salary range for this role is $200,000 to $300,000, adjusted based on experience, skills, qualifications, and geographic location
Total compensation may include equity in the form of stock options
A confirmation email will be sent upon successful application submission. If no confirmation is received, contact careers@fluidstack.io with your resume/CV, the position applied for, and the application date

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Fluidstack is hiring a System Engineer, GPU Fleet