Cloud Storage Integration Engineer (Storage / Image / Registry)

Key Responsibilities

• Design and integrate distributed / parallel file systems (e.g. Ceph, Lustre, GPFS / Spectrum Scale, BeeGFS, JuiceFS) into the GPU cloud, optimized for AI training / inference I/O patterns.
• Own end-to-end distributed-storage integration: provisioning, mounting, multi-tenant isolation, quota, and lifecycle within the platform / control plane.
• Tune storage throughput and latency for large-scale parallel access (dataset loading, checkpointing); benchmark across GPU SKUs and workloads.
• Architect multi-region storage: data locality, replication / consistency, durability (failure domains), and cross-region access.
• Own golden images, templates, GPU drivers / CUDA, and the container / image registry, including versioned release and multi-region distribution.

Job Requirement

• 3+ years (Senior 6+) in storage engineering or platform infrastructure, with hands-on distributed / parallel file system experience.
• Strong understanding of distributed file system internals — data / metadata separation, replication, consistency models, POSIX vs object semantics.
• Proven experience integrating and operating distributed storage in production (e.g. Ceph, Lustre, GPFS / Spectrum Scale, BeeGFS, JuiceFS, MinIO).
• Performance tuning for high-throughput / parallel I/O; familiarity with NVMe, RDMA / RoCE storage networking, and caching is a strong plus.
• Strong Linux systems depth and automation skills (Python / Go, CI / CD).
• HPC / AI storage or multi-region storage experience a strong plus.