Senior Storage Systems Architect for AI/ML & HPC

NVIDIA; Sydney; On-site; AUD 180,000 - 240,000; Full time

Job summary

NVIDIA Storage Production Engineers design, implement, and support large-scale storage clusters, ensuring scalability and data integrity for GPU cloud services. You’ll develop monitoring, logging, and alerting systems and work with AI/ML workloads to optimize low-latency access and high throughput.

You will drive lifecycle improvements from design to deployment, maintain production infrastructure, and participate in on-call rotation while advancing security and efficiency in a fast-paced

Qualifications

• BS degree or equivalent experience in Computer Science, Storage Systems, or a related technical field with 8+ years of practical experience.
• Experience with distributed and high-performance storage solutions, including clustered and parallel file systems, distributed object storage, and enterprise-grade storage systems.
• Solid understanding of block, file, and object storage technologies, including their scalability, reliability, and performance characteristics.
• Experience with storage networking protocols such as NFS, SMB, iSCSI, S3, Fibre Channel, RDMA, and NVMe over Fabrics.
• Expertise in algorithms, data structures, complexity analysis, software design, and automating maintenance of large-scale Linux-based storage systems.
• Experience in one or more of the following: C/C++, Java, Python, Go, NodeJS, and Bash for storage automation, monitoring, and performance tuning.
• Hands-on experience with infrastructure configuration management tools and observability stacks.

Responsibilities

• Design, implement, and support large-scale storage clusters, ensuring scalability, high availability, and data integrity.
• Develop and maintain storage monitoring, logging, and alerting systems to ensure proactive detection and resolution of performance issues.
• Work with AI/ML workloads to improve storage architectures for low-latency access, efficient caching, and high-throughput performance.
• Improve the lifecycle of storage services – from inception and design to deployment, operation, and continuous optimization.
• Maintain production storage infrastructure by supervising availability, latency, and system health, leveraging predictive analytics and AI-driven automation.
• Optimize storage efficiency through compression, deduplication, tiering strategies, and intelligent workload placement.
• Scale storage systems sustainably using AI/ML-driven automation, policy-based tiering, and dynamic data migration techniques.
• Ensure data security and compliance by implementing encryption, access controls, and auditing mechanisms for storage systems.
• Practice sustainable incident response and blameless root cause analysis. Be part of an on-call rotation to support storage and production systems.

Skills

Distributed storage systems

High-performance storage

Linux

Automation

C/C++

Python

Go

CI/CD

Education

BS degree in Computer Science or related field

Tools

Ansible

Chef

Puppet

Terraform

InfluxDB/Prometheus/Grafana/Elastic

Job description

NVIDIA Storage Production Engineers design, implement, and support large-scale storage clusters, ensuring scalability and data integrity for GPU cloud services. You’ll develop monitoring, logging, and alerting systems and work with AI/ML workloads to optimize low-latency access and high throughput.

You will drive lifecycle improvements from design to deployment, maintain production infrastructure, and participate in on-call rotation while advancing security and efficiency in a fast-paced