Senior Storage Systems Engineer — AI Infra (Exascale)

NVIDIA Corporation; Redmond; On-site; AUD 219,000 - 414,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA in Australia is seeking an experienced Senior Systems Engineer for the Managed AI Research Superclusters (MARS) to design and operate large-scale AI infrastructure across multi-region GPU clusters. You will drive scalable data, compute, and networking solutions for demanding workloads.

The role requires 5+ years in distributed systems, strong C++, Python, or Go skills, and hands-on experience with Lustre/GPFS storage and Slurm/Kubernetes.

Qualifications

• BS or equivalent experience in Computer Science or related field.
• 5+ years in large-scale distributed systems or HPC environments.
• Strong programming in C++, Python, or Go.
• Solid understanding of distributed systems and orchestration.
• Hands-on storage and compute scheduling experience (Lustre/GPFS, Slurm, Kubernetes, LSF).
• Familiar with cloud environments (Azure, AWS, GCP).
• Strong problem-solving and collaboration skills.
• Excellent communication and cross-functional teamwork.

Responsibilities

• Design, develop, and operate distributed AI infrastructure.
• Build automation to orchestrate workloads across GPUs and storage.
• Collaborate with AI/ML research teams to translate needs into scalable solutions.
• Improve reliability, performance, and observability to exascale standards.
• Partner with security, networking, and platform teams for robust systems.
• Participate in design reviews and system architecture discussions.
• Stay current with distributed systems and AI framework advances.

Skills

Distributed systems

High performance computing

C++

Python

Go

Education

BS in Computer Science or related

Tools

Lustre

GPFS

BeeGFS

Slurm

Kubernetes

LSF

Azure

AWS

GCP

Job description

NVIDIA in Australia is seeking an experienced Senior Systems Engineer for the Managed AI Research Superclusters (MARS) to design and operate large-scale AI infrastructure across multi-region GPU clusters. You will drive scalable data, compute, and networking solutions for demanding workloads.

The role requires 5+ years in distributed systems, strong C++, Python, or Go skills, and hands-on experience with Lustre/GPFS storage and Slurm/Kubernetes.