Frontier AI Storage Infrastructure Engineer

Matcha

Northern (KY)

Hybrid

USD 150,000 - 300,000

Full time

7 days ago
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Job summary

Prime Intellect is building the open superintelligence stack, delivering scalable storage for frontier AI workloads. You will design and operate storage architectures feeding datasets, checkpoints, and artifacts, balancing performance, durability, and cost as GPU clusters scale.

You will deploy parallel filesystems and object storage, benchmark performance, and drive automation for reliable, high-throughput storage systems in a cutting-edge AI environment.

Qualifications

  • 3+ years building or operating production distributed storage systems.
  • Hands-on with parallel/file/object storage platforms such as Lustre/Ceph/GPFS.
  • Strong Linux administration and performance troubleshooting.
  • Experience automating infra ops with Python, Go, or Bash.
  • Understanding of data integrity, replication, and recovery.

Responsibilities

  • Design and operate storage architectures for training datasets, checkpoints, and artifacts.
  • Deploy and tune parallel filesystems, object storage, and NVMe caching for AI workloads.
  • Benchmark throughput, latency, and metadata performance under representative workloads.
  • Build provisioning, capacity planning, lifecycle management, and automation for storage services.
  • Design and test replication, recovery, backup, and durability targets.
  • Diagnose performance and reliability issues across applications, networks, and storage devices.
  • Implement access controls, quotas, monitoring, and runbooks; collaborate with compute/network teams.

Skills

Distributed storage concepts
Linux administration
Performance troubleshooting
Python scripting

Tools

Lustre
BeeGFS
Ceph
GPFS

Job description

Prime Intellect is building the open superintelligence stack, delivering scalable storage for frontier AI workloads. You will design and operate storage architectures feeding datasets, checkpoints, and artifacts, balancing performance, durability, and cost as GPU clusters scale.

You will deploy parallel filesystems and object storage, benchmark performance, and drive automation for reliable, high-throughput storage systems in a cutting-edge AI environment.

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