Senior AI Storage Infrastructure Engineer
Bitdeer Technologies Group is a technology company providing Bitcoin mining solutions, SEALMINER mining equipment, cloud mining, AI cloud infrastructure, high-performance computing, and data-center services. Its customers include miners, developers, AI and machine-learning users, and institutional customers.
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About Bitdeer Technologies Group
Bitdeer Technologies Group operates across Bitcoin mining, AI cloud, and data-center infrastructure. Its offerings include proprietary SEALMINER equipment, Minerbase cooling systems, cloud-mining plans, co-mining services, mining-farm management tools, and mobile apps. The company also provides GPU-based AI and high-performance computing services for model training and deployment, as well as turnkey AI data-center solutions. Bitdeer is headquartered in Singapore and operates globally, with major operations in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.
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Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will architect the storage data-delivery fabric for intensive AI training and inference workloads. You will develop CSI drivers, integrate GPUDirect Storage, manage NVMe caching, tune I/O performance, optimize RDMA connectivity, implement storage monitoring and quotas, and enforce multi-tenant resource isolation.
Requirements
- Bachelor’s or Master’s degree in Computer Science Electrical Engineering or a related field
- 5+ years of experience with distributed storage and high-performance file systems
- Understanding of POSIX compliance and file I/O semantics
- Deep expertise in Kubernetes CSI including volume plugins and storage operators
- Experience with Linux block and file I/O and kernel performance tuning
- Familiarity with RDMA InfiniBand and RoCE
- Experience operating debugging and scaling production or HPC storage environments
- Experience with Terraform Ansible and CI/CD pipelines
- Strong technical communication skills
Responsibilities
- Design and maintain CSI drivers for high-performance parallel file systems
- Implement GPUDirect Storage integrations
- Develop local NVMe caching strategies for models and datasets
- Optimize IOPS throughput and latency across the storage stack
- Integrate storage with RDMA InfiniBand and RoCE networks
- Implement storage performance monitoring and alerting
- Define storage policies quotas and Kubernetes multi-tenancy isolation
- Mentor engineers and lead architectural design reviews