Senior Storage Infrastructure Engineer for AI/ML & HPC

Nvidia; New South Wales; On-site; AUD 180,000 - 240,000; Full time

Job summary

NVIDIA is seeking a Production Storage Engineer to design, deploy, and optimize large-scale storage systems for GPU cloud services. You will focus on high availability, low latency, and data integrity across distributed storage environments, supporting AI/ML workflows and enterprise-grade storage deployments.

You will automate operations, monitor performance with the Elastic Stack and Prometheus, and lead capacity planning while maintaining strict security and compliance.

Qualifications

• BS degree or equivalent in Computer Science, Storage Systems, or related field with 8+ years practical experience.
• Experience with distributed and high‑performance storage solutions including clustered/parallel file systems and enterprise storage.
• Solid understanding of block, file, object storage and their performance characteristics.
• Experience with storage networking protocols such as NFS, SMB, iSCSI, S3, Fibre Channel, RDMA, NVMe over Fabrics.
• Expertise in algorithms, data structures, software design, and automating maintenance of large-scale Linux‑based storage systems.
• Experience in one or more: C/C++, Java, Python, Go, NodeJS, Bash for storage automation and tuning.
• Hands-on with Ansible, Chef, Puppet, Terraform for automating deployments; observability with InfluxDB, Prometheus, Grafana, Elastic Stack.
• Excellent written and oral communication; strong teamwork and commitment to daily delivery.

Responsibilities

• Design, build, and support large-scale storage clusters ensuring scalability, high availability, and data integrity.
• Develop and maintain storage monitoring, logging, and alerting systems for proactive issue resolution.
• Collaborate on AI/ML workloads to optimize storage for low latency and high throughput.
• Enhance storage service lifecycles from design to deployment and ongoing optimization.
• Supervise production storage infrastructure, monitor latency and system health using predictive analytics and automation.
• Improve storage efficiency via compression, deduplication, tiering, and intelligent workload placement.
• Scale storage with AI/ML automation and secure data access with encryption and auditing.
• Participate in on-call rotations for storage and production system reliability.

Skills

Distributed storage

High-performance storage

Automation

Linux

C/C++

Python

Go

Networking

Data management

Block/File/Object storage

Education

BS degree or equivalent in Computer Science/Storage Systems

Tools

Ansible

Chef

Puppet

Terraform

InfluxDB

Prometheus

Grafana

Elastic stack

Job description

NVIDIA is seeking a Production Storage Engineer to design, deploy, and optimize large-scale storage systems for GPU cloud services. You will focus on high availability, low latency, and data integrity across distributed storage environments, supporting AI/ML workflows and enterprise-grade storage deployments.

You will automate operations, monitor performance with the Elastic Stack and Prometheus, and lead capacity planning while maintaining strict security and compliance.