Member of Technical Staff - Storage Infrastructure

Summary

Prime Intellect is building an open superintelligence infrastructure stack for frontier AI research and production workloads. The Member of Technical Staff will build and operate reliable, high-throughput storage systems for datasets, checkpoints, and model artifacts, while managing performance, durability, availability, security, and cost at GPU-cluster scale.

Responsibilities

• Design and operate storage architectures for training datasets, checkpointing, inference artifacts, and shared research workflows
• Deploy and tune parallel filesystems, object storage, and local NVMe caching for demanding AI workloads
• Benchmark throughput, latency, metadata performance, and concurrent access with representative training and checkpoint workloads
• Build provisioning, capacity planning, lifecycle management, and operational automation for storage services
• Design and test replication, recovery, backup, and failure-handling procedures with explicit durability and availability targets
• Diagnose performance and reliability issues across applications, clients, networks, filesystems, and devices
• Implement access controls, tenant separation, quotas, monitoring, and runbooks; collaborate with compute and networking teams

Skills

• • 3+ years building or operating production distributed storage systems
• • Hands-on experience with at least one parallel or distributed filesystem or object storage platform, such as Lustre, BeeGFS, Ceph, or GPFS
• • Strong Linux administration and performance troubleshooting skills
• • Experience automating infrastructure operations in Python, Go, Bash, or similar languages
• • Understanding of storage failure modes, data integrity, consistency, replication, and recovery
• • Block, file, and object storage semantics and their performance tradeoffs
• • NVMe/SSD performance, filesystem tuning, I/O profiling, and benchmarking
• • High-throughput storage networking and distributed client behavior
• • Capacity forecasting, observability, alerting, and safe maintenance procedures
• • Authentication, authorization, encryption, and secure data lifecycle management
• • Experience supporting large GPU training clusters and high-volume checkpoint workloads
• • S3-compatible object storage, data tiering, or distributed caching
• • RDMA-enabled storage or GPUDirect Storage experience
• • Kubernetes storage integrations or SLURM environments
• • Storage cost optimization and contributions to open-source storage systems

Qualifications

Must Haves

• • 3+ years building or operating production distributed storage systems
• • Hands-on experience with at least one parallel or distributed filesystem or object storage platform, such as Lustre, BeeGFS, Ceph, or GPFS
• • Strong Linux administration and performance troubleshooting skills
• • Experience automating infrastructure operations in Python, Go, Bash, or similar languages
• • Understanding of storage failure modes, data integrity, consistency, replication, and recovery
• • Block, file, and object storage semantics and their performance tradeoffs
• • NVMe/SSD performance, filesystem tuning, I/O profiling, and benchmarking
• • High-throughput storage networking and distributed client behavior
• • Capacity forecasting, observability, alerting, and safe maintenance procedures
• • Authentication, authorization, encryption, and secure data lifecycle management

Nice to Haves

• • Experience supporting large GPU training clusters and high-volume checkpoint workloads
• • S3-compatible object storage, data tiering, or distributed caching
• • RDMA-enabled storage or GPUDirect Storage experience
• • Kubernetes storage integrations or SLURM environments
• • Storage cost optimization and contributions to open-source storage systems

Benefits

• Equity incentives