Senior AI Storage Engineer for GPU-Intensive Training

Bitdeer Technologies Group; Austin (TX); On-site; USD 170,000 - 210,000; Full time

Job summary

Bitdeer Technologies Group in Austin, TX is seeking a Senior AI Storage Infrastructure Engineer to design and deploy high‑performance storage for AI workloads. You will build the data delivery fabric supporting large-scale distributed training and inference, spanning NVMe caching, parallel file systems, and Kubernetes orchestration.

You will own CSI drivers, GPUDirect Storage integrations, and multi‑tenancy storage policies while collaborating with the GPU Systems & Fabric teams to optimize RDMA

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
• 5 years of experience in distributed storage systems and high-performance file systems, with a deep understanding of POSIX compliance and file I/O semantics.
• Deep expertise in the Kubernetes CSI paradigm, including building or extending volume plugins and storage operators.
• Strong hands-on experience with block/file I/O at the Linux OS level and kernel-level performance tuning.
• Familiarity with high-throughput networking protocols (RDMA, InfiniBand, RoCE) and how they interact with storage subsystems.
• Proven track record of operating, debugging, and scaling large-scale storage environments in production or HPC settings.
• Experience with infrastructure automation tools (e.g., Terraform, Ansible) and CI/CD pipelines.
• Excellent technical communication skills, with the ability to influence cross-functional architectural decisions.
• Experience working in high-velocity, high-growth engineering environments is strongly preferred.

Responsibilities

• Design, deploy, and maintain CSI drivers for high-performance parallel file systems.
• Architect and implement GPUDirect Storage (GDS) integrations to enable DMA between NVMe drives and GPU memory.
• Develop and manage local NVMe caching strategies for rapid loading of large model weights and datasets.
• Optimize IOPS, throughput, and latency across the containerized storage stack.
• Collaborate with the GPU Systems & Fabric team to ensure storage is optimized for RDMA and high-speed interconnects.
• Implement automated monitoring and alerting for storage performance and hardware degradation.
• Define storage policies, quota management, and multi-tenancy isolation within Kubernetes.
• Mentor junior engineers and drive architectural design reviews.

Skills

Kubernetes CSI

Kernel I/O tuning

Linux block I/O

Technical communication

Mentoring

Education

Bachelors or Masters in CS/EE

Tools

Terraform

Ansible

CI/CD

Weka

Lustre

DAOS

VAST

RDMA networking

Job description

Bitdeer Technologies Group in Austin, TX is seeking a Senior AI Storage Infrastructure Engineer to design and deploy high‑performance storage for AI workloads. You will build the data delivery fabric supporting large-scale distributed training and inference, spanning NVMe caching, parallel file systems, and Kubernetes orchestration.

You will own CSI drivers, GPUDirect Storage integrations, and multi‑tenancy storage policies while collaborating with the GPU Systems & Fabric teams to optimize RDMA