Senior AI Storage Infrastructure Engineer

About the role

Bitdeer is looking for a Senior AI Storage Infrastructure Engineer to design, deploy and maintain high‑performance storage solutions for AI and HPC workloads. You will work on cutting‑edge parallel file systems and GPU‑direct storage integrations within a global, multi‑datacenter environment.

Key responsibilities

• Design, develop and support Container Storage Interface (CSI) drivers for parallel file systems such as Weka, Lustre, DAOS and VAST.
• Implement GPUDirect Storage (GDS) to enable DMA between NVMe drives and GPU memory, eliminating CPU bottlenecks.
• Create 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, from storage arrays to container runtimes.
• Collaborate with GPU Systems & Fabric teams to ensure storage is tuned for RDMA, InfiniBand and RoCE interconnects.
• Build automated monitoring, alerting and health‑checking for storage performance and hardware health.
• Define storage policies, quota management and multi‑tenant isolation within Kubernetes.
• Mentor junior engineers and lead architectural design reviews.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering or a related field.
• 5+ years of experience with distributed storage systems and high‑performance file systems.
• Proven track record operating, debugging and scaling large‑scale storage environments in production or HPC settings.
• Strong understanding of POSIX compliance, file I/O semantics and Linux kernel‑level performance tuning.

Required skills

• Container Storage Interface (CSI) development
• Kubernetes storage operators and volume plugins
• Parallel file systems: Weka, Lustre, DAOS, VAST
• GPUDirect Storage (GDS) and NVMe technologies
• RDMA, InfiniBand, RoCE networking protocols
• Linux OS and kernel performance tuning
• Infrastructure automation: Terraform, Ansible
• CI/CD pipeline integration