Cloud Storage Integration Engineer (Storage / Image / Registry)

Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.

Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.

Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.

To learn more, visit https://ir.bitdeer.com/

GPU training and inference at 10,000+ GPU, multi-region scale depend on high-throughput, low-latency storage that can sustain massive parallel I/O. We are looking for an engineer who deeply understands distributed file systems and can integrate distributed / parallel storage systems into our GPU cloud — covering performance, multi-tenancy, and reliability — while also owning the image / driver / registry pipeline on the node-delivery critical path.

• →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. (Secondary scope.)
• →Build monitoring, capacity planning, and runbooks; eliminate single points of failure.
• →Partner with Compute (delivery), Network (storage fabric / RDMA), and Control Plane (provisioning / quota) teams.

• 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.

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