Distributed Storage Engineer for AI/GPU Cloud

Bitdeer Technologies Group

Austin (TX)

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

Bitdeer Technologies Group in Austin is seeking an experienced storage infrastructure engineer to design and integrate distributed file systems for AI training workloads within a multi-region GPU cloud. You will own end-to-end storage integration, provisioning, and performance tuning to support massive I/O patterns.

The role requires deep Linux expertise, strong automation (Python/Go), and production experience with Ceph, Lustre, GPFS, BeeGFS, JuiceFS, or MinIO.

Qualifications

3+ years (Senior 6+) in storage engineering or platform infrastructure.
Hands-on distributed/parallel file system experience.
Production experience with Ceph, Lustre, GPFS/Spectrum Scale, BeeGFS, JuiceFS, or MinIO.
Strong Linux and automation skills (Python/Go).
HPC/AI storage or multi-region storage experience is a plus.

Responsibilities

Design and integrate distributed / parallel file systems 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; benchmark across GPU SKUs and workloads.
Architect multi-region storage: data locality, replication / consistency, durability, and cross-region access.
Own golden images, templates, GPU drivers / CUDA, and the container / image registry, including versioned release and multi-region distribution.
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.