GPU Cloud Storage Engineer — Distributed FS & Registry

Bitdeer (NASDAQ: BTDR); San Jose (CA); On-site; USD 150,000 - 190,000; Full time

Job summary

Bitdeer Technologies Group seeks an experienced storage infra engineer to design and integrate distributed/parallel file systems into its GPU cloud for AI training and inference at scale.

You will own end-to-end storage integration, tune throughput/latency, architect multi-region data distribution, and manage images, drivers, and registries while collaborating with Compute, Network, and Control Plane teams.

Qualifications

• 3+ years in storage engineering or platform infrastructure, senior level 6+
• Deep understanding of distributed file system internals—data/metadata, replication, consistency
• Production experience with distributed storage (Ceph, Lustre, GPFS/Spectrum Scale, BeeGFS, JuiceFS, MinIO)
• Performance tuning for high-throughput parallel I/O; NVMe / RDMA knowledge a plus
• Strong Linux depth and automation skills (Python / Go, CI/CD)
• HPC/AI storage or multi-region storage experience is a strong plus

Responsibilities

• Design and integrate distributed/parallel file systems into GPU cloud for AI training/inference
• Own end-to-end distributed-storage integration: provisioning, mounting, multi-tenant isolation, quotas
• Tune storage throughput/latency for large-scale parallel access across GPU SKUs
• Architect multi-region storage with data locality, replication, durability, cross-region access
• Own golden images, templates, GPU drivers/CUDA, and container/image registry distribution
• Build monitoring, capacity planning, and runbooks; partner with Compute/Network/Control Plane teams

Skills

Distributed file systems

Python

Go

Linux

CI/CD

Performance tuning

Tools

Ceph

Lustre

GPFS/Spectrum Scale

BeeGFS

JuiceFS

MinIO

Job description

Bitdeer Technologies Group seeks an experienced storage infra engineer to design and integrate distributed/parallel file systems into its GPU cloud for AI training and inference at scale.

You will own end-to-end storage integration, tune throughput/latency, architect multi-region data distribution, and manage images, drivers, and registries while collaborating with Compute, Network, and Control Plane teams.