Senior AI/HPC Networking Architect - InfiniBand & Ethernet

NVIDIA Corporation

Australia

Remote

AUD 180,000 - 260,000

Full time

14 days+

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Job summary

NVIDIA is seeking a Senior Networking (ETH/IB) Solutions Architect to join its Infrastructure Specialist Team in Australia. The role focuses on building AI/HPC infrastructure for large-scale customers, maintaining high performance and reliability, and driving end-to-end lifecycle improvements.

You will interact with customers, partners, and internal teams to implement complex networking projects. The candidate should have 5+ years in networking, hands-on experience with Ethernet/InfiniBand,

Qualifications

BS/MS/PhD or equivalent experience in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields.
At least 5+ years of professional experience in networking fundamentals, Ethernet or InfiniBand World.
Hands-on experience with network switch/router platforms like Cumulus Linux, SONiC, IOS, JunosOS, and EOS, etc.
Possess solid working knowledge of Ethernet/InfiniBand/RDMA core principles.
Be proficient in end-to-end IB/Eth cluster deployment, adapter configuration and firmware maintenance, and able to conduct professional performance benchmarking with mainstream RDMA testing tools.
Capable of independently diagnosing and troubleshooting typical IB/Eth network anomalies, including link flapping, connection failure, as well as bandwidth and latency jitter issues.
Master practical RDMA network optimization strategies such as QP tuning, MTU configuration and congestion control optimization.
Hands-on working experience in RDMA-accelerated business scenarios, including distributed storage and high-performance computing clusters.
Extensive experience delivering automated network provisioning solutions using tools like Ansible, Salt, and Python.
Ability to develop CI/CD pipelines for network operations.
Strong written, verbal, and listening skills in English are essential.

Responsibilities

Building AI/HPC infrastructure for new and existing customers.
Support operational and reliability aspects of large-scale AI clusters, focusing on performance at scale, real-time monitoring, logging, and alerting.
Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation, and refinement.
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health.
Provide feedback to internal teams such as opening bugs, documenting workarounds, and suggesting improvements.