Sr. GPU Cloud Storage Solutions Expert (SRE SME)

Bitdeer Technologies Group; Singapore; On-site; SGD 120,000 - 160,000; Full time

Benefits offered by this job

Welfare benefits

Training & mentoring

Development opportunities

Job summary

Bitdeer Technologies Group is seeking a storage-focused engineer to deploy and operate high-performance storage systems for AI workloads. You will design architectures optimized for AI data patterns, implement multi-tenant QoS, and manage storage networking for GPU clusters.

Strong Linux, benchmarking, and automation mindset are essential. In this role, you will partner with the platform team to instrument telemetry, build runbooks-as-code, and drive observability improvements.

Qualifications

• 5+ years in storage operations for enterprise or HPC environments.
• Experience supporting AI/ML workloads and high-performance storage networks.
• Experience implementing multi-tenant storage with QoS and isolation.
• Strong Linux systems knowledge including kernel tuning and filesystem internals.

Responsibilities

• Deploy and operate storage systems (WEKA, VAST Data, Ceph, DDN/Lustre) optimized for AI workloads.
• Design AI-oriented storage architectures for patterns like checkpoint I/O bursts and fast dataset reads.
• Implement multi-tenant storage isolation with QoS, quotas, and access controls; optimize GPU Direct Storage.
• Deploy and manage storage networking (NFS over RDMA, NVMe-oF) and Nvidia CMX for orchestration.
• Diagnose and tune storage performance using fio/IOR/mdtest; maintain runbooks for common failures.
• Plan capacity for GPU clusters and manage firmware, data migration, and DR procedures.
• Instrument telemetry (latency, checkpoint times, NVMe SMART) and feed to metrics/logs.
• Collaborate to define storage-fault predictor signals and labels; convert incidents into automation.
• Develop observability baselines and reduce MTTR for storage incidents.
• Ensure new Nvidia GB200-class clusters align with the storage architecture.

Skills

Storage operations

AI/ML workloads

Observability

Performance benchmarking

Multi-tenant QoS

Linux systems

Tools

WEKA

VAST Data

Ceph

DDN/Lustre

NFS over RDMA

NVMe-oF

GPU Direct Storage

fio

IOR

mdtest

Kernel tuning

Filesystem internals

Block device management

Job description

About Bitdeer:

Bitdeer is a world-leading technology company for Bitcoin mining and AI cloud. Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers. Apart from designing industry-leading ASIC chips and manufacturing mining rigs, the Group handles complex processes involved in computing across the value chain. This includes equipment procurement, transport logistics, datacenter design and construction, equipment management, and network and facility operations. Bitdeer also offers advanced cloud capabilities to customers with a high demand for artificial intelligence. Headquartered in Singapore, Bitdeer operates globally with a diversified 3 GW energy portfolio, and deploys Bitcoin mining and HPC datacenters in the United States, Bhutan, Norway, Canada, Malaysia, and Ethiopia.

What you will be responsible for:

What you'll own

• Deploy and operate parallel/distributed storage systems: WEKA, VAST Data, Ceph, DDN/Lustre. Design storage architectures optimized for AI workload patterns — checkpoint I/O bursts, sequential dataset reads, KV cache for inference.
• Implement multi-tenant storage isolation with per-tenant QoS, quotas, and access controls; configure and optimize GPU Direct Storage for direct GPU-to-storage data paths.
• Deploy and manage storage networking (NFS over RDMA, NVMe-oF, high-speed storage fabrics) and Nvidia CMX for cluster-wide storage orchestration.
• Diagnose and tune storage performance: IOPS, throughput, latency profiling with fio, IOR, mdtest; own the runbook for common failure modes.
• Plan storage capacity aligned with GPU cluster growth and customer workload projections; manage firmware, data migration, and DR procedures.

Feed the AIOps substrate

• Instrument storage telemetry — IO tail latency, checkpoint durations, NVMe SMART, filesystem health, RDMA counters — into the metrics/logs/traces store the platform team runs.
• Partner with the platform team to define the storage-fault predictor: which signals, which labels (from your incidents), which false-positive tolerances.
• Convert every novel incident into an automation: SOPs become runbook-as-code, runbook-as-code becomes an agent-executable remediation.

What success looks like in year 1

• Observability and a baseline predictor for the top 3 storage-fault classes on our fabric.
• Storage-incident MTTR measurably lower than at hire.
• The Nvidia GB200-class clusters we build out ship on your storage design.

How you will stand out:

• 5+ years in enterprise or HPC storage operations, with at least 2 years supporting AI/ML workloads
• Hands‑on deployment and operations experience with at least two of: WEKA, VAST Data, Ceph, DDN/Lustre
• Strong understanding of AI training I/O patterns: checkpoint frequency, dataset loading, shuffle buffers
• Experience with high-performance storage networking (NFS over RDMA, NVMe-oF)
• Knowledge of GPU Direct Storage and RDMA-based data transfer
• Proficiency in storage performance benchmarking and tuning (fio, IOR, mdtest)
• Experience implementing multi-tenant storage with isolation and QoS
• Strong Linux systems knowledge (kernel tuning, filesystem internals, block device management)
• Instinct for turning ops toil into ML signal — you've either shipped an anomaly detector for storage/IO telemetry or you can articulate the labels and features you'd need to.
• Runbook-as-code mindset — every SOP you write should be executable by a machine within a quarter

What you will experience working with us:

• A culture that values authenticity and diversity of thoughts and backgrounds;
• An inclusive and respectable environment with open workspaces and exciting start-up spirit;
• Fast-growing company with the chance to network with industrial pioneers and enthusiasts;
• Ability to contribute directly and make an impact on the future of the digital asset industry;
• Involvement in new projects, developing processes/systems;
• Personal accountability, autonomy, fast growth, and learning opportunities;
• Attractive welfare benefits and developmental opportunities such as training and mentoring.

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Bitdeer is committed to providing equal employment opportunities in accordance with country, state, and local laws. Bitdeer does not discriminate against employees or applicants based on conditions such as race, colour, gender identity and/or expression, sexual orientation, marital and/or parental status, religion, political opinion, nationality, ethnic background or social origin, social status, disability, age, indigenous status, and union.

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