System Engineer, GPU Fleet

Overview

About Fluidstack:
At Fluidstack, we’re building the infrastructure for abundant intelligence. We partner with top AI labs, governments, and enterprises to unlock compute at the speed of light. We’re working with urgency to make AGI a reality and are looking for motivated individuals who are committed to delivering world-class infrastructure.

If you’re motivated by purpose, obsessed with excellence, and ready to work very hard to accelerate the future of intelligence, join us in building what's next.

As a System Engineer, GPU Fleet, you will manage, operate, and optimize hyperscale GPU compute infrastructure supporting AI/ML training and inference workloads. Ensure high availability, performance, and reliability of the GPU server fleet through automation, monitoring, troubleshooting, and collaboration with hardware engineering, platform teams, and datacenter operations.

• Operate and maintain a large-scale GPU server fleet (H100, B200, GB200) supporting AI/ML workloads; monitor system health, performance, and utilization to maximize uptime and ensure SLA compliance.
• Perform hands-on troubleshooting and root cause analysis of complex hardware, firmware, OS, and application issues across GPU clusters; coordinate with vendors and hardware teams to resolve systemic failures.
• Develop and maintain automation scripts for provisioning, configuration management, monitoring, and remediation at scale.
• Build and improve tooling for GPU health checks, performance diagnostics, driver validation, and automated recovery.
• Execute server provisioning, configuration, firmware updates, and OS installation using automation frameworks; manage lifecycle operations including deployment, maintenance, and decommissioning.
• Participate in 24x7 on-call rotation; respond to production incidents and coordinate resolution with cross-functional teams including datacenter operations, network engineering, and application teams.
• Lead post-incident reviews, document root causes, and drive continuous improvement initiatives focused on automation, reliability, monitoring, and operational efficiency.

• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience).
• 3+ years (System Engineer) or 5+ years (Senior System Engineer) in Linux system administration, datacenter operations, or infrastructure engineering.
• Strong Linux/Unix fundamentals including system administration, shell scripting (Bash, Python), troubleshooting, and performance tuning.
• Experience with server hardware architecture, troubleshooting techniques, and understanding of compute, memory, storage, and networking components.
• Experience in automation and configuration management tools (Ansible, Puppet, Chef, Terraform).
• Strong analytical and problem-solving skills with ability to diagnose complex technical issues under pressure.
• Excellent communication and collaboration skills; ability to work effectively with cross-functional teams.

• Experience managing large-scale GPU infrastructure (NVIDIA H100, A100, B200, GB200) in production environments supporting AI/ML workloads.
• Deep knowledge of GPU architecture, CUDA toolkit, GPU drivers, monitoring tools (nvidia-smi, DCGM).
• Experience with HPC cluster management, job schedulers (Slurm, PBS, LSF), and container orchestration (Kubernetes, Docker).
• Proficiency in out-of-band management protocols (IPMI, Redfish, BMC) and firmware management for server hardware.
• Experience with high-performance networking (Infini Band, RoCE, RDMA) and network troubleshooting in GPU cluster environments.
• Familiarity with datacenter operations including rack installations, cabling, power management, and thermal considerations.

• Competitive total compensation package (salary + equity).
• Retirement or pension plan, in line with local norms.
• Health, dental, and vision insurance.
• Generous PTO policy, in line with local norms.

The base salary range for this position is $200,000 - $300,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role…