Job description

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for phenomenal people like you to help us accelerate the next wave of artificial intelligence. We are looking for highly motivated Senior Software Engineers to join our Fabric Networking team with a targeted focus on NVLink Rack-Scale Systems Stability & Reliability. In this role, you will partner closely with architects and developers building our next-generation NVLink and NVSwitch systems, helping transform first-of-their-kind platforms into stable, reliable, and volume production-ready systems. You will work on complex system-level challenges spanning resiliency, diagnostics, recovery, and large-scale AI infrastructure, contributing directly to the software foundation powering next-generation datacenter deployments. What you will be doing: • Drive platform bringup, feature enablement, end-to-end software validation, and debug for next-generation NVLink-based GPU and rack-scale systems. • Develop tools, diagnostics, automation, and infrastructure for system validation, regression testing, and fleet support. • Lead reliability and MTBI validation through stress testing, telemetry analysis, failure injection, and issue resolution. • Triage complex software, firmware, networking, and platform issues across validation, deployment, and production environments. • Collaborate with architecture, hardware, firmware, software, and Customer engagement teams to improve system quality and reliability. • Build and maintain SRE-style validation infrastructure, including provisioning, monitoring, and operational readiness. • Create automation, dashboards, runbooks, and debug workflows that improve root-cause analysis and operational efficiency. What we need to see: • BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience. • 5+ years of experience in system software, firmware, networking, platform enablement, data center infrastructure, or distributed systems. • Strong programming skills in C/C++ and Python; Bash/Shell scripting experience is a plus. • Strong system-level debugging across software, firmware, hardware, and networking layers. • Solid networking fundamentals, including TCP/IP, Ethernet and/or InfiniBand, RDMA/RoCE, routing, switching, and fabric performance analysis. • Experience with large-scale AI systems, including platform bringup, validation, reliability engineering, stress testing, telemetry analysis, and root-cause debugging. • Ability to triage complex multi-domain issues using logs, telemetry, experiments, and structured debugging methods. • Strong communication and collaboration skills across engineering, customer, and operations teams. Passion for building reliable next-generation AI infrastructure and solving complex system-level challenges at scale. Ways to stand out from the crowd: • Experience with NVIDIA GPU systems, NVLink, NVSwitch, CUDA, and large-scale AI/HPC clusters such as NVIDIA GB200 NVL72. • Strong understanding of large-scale AI system architecture, including PCIe, memory hierarchy, DMA, high-speed interconnects, and distributed training/inference systems. • Experience with server management technologies, data center operations, cluster provisioning, scaling, and fleet monitoring. • Proven experience building diagnostics, automation, CI/CD pipelines, dashboards, and reliability tooling.

Requirements

Must-haves

Drive platform bringup, feature enablement, end-to-end software validation, and debug for next-generation NVLink-based GPU and rack-scale systems.
Develop tools, diagnostics, automation, and infrastructure for system validation, regression testing, and fleet support.
Lead reliability and MTBI validation through stress testing, telemetry analysis, failure injection, and issue resolution.
Triage complex software, firmware, networking, and platform issues across validation, deployment, and production environments.
Collaborate with architecture, hardware, firmware, software, and Customer engagement teams to improve system quality and reliability.
Build and maintain SRE-style validation infrastructure, including provisioning, monitoring, and operational readiness.
Create automation, dashboards, runbooks, and debug workflows that improve root-cause analysis and operational efficiency.
BS or MS in Computer Science, Computer Engineering, Electrical Engineering, or related field, or equivalent experience.
5+ years of experience in system software, firmware, networking, platform enablement, data center infrastructure, or distributed systems.
Strong system-level debugging across software, firmware, hardware, and networking layers.
Solid networking fundamentals, including TCP/IP, Ethernet and/or InfiniBand, RDMA/RoCE, routing, switching, and fabric performance analysis.
Experience with large-scale AI systems, including platform bringup, validation, reliability engineering, stress testing, telemetry analysis, and root-cause debugging.
Ability to triage complex multi-domain issues using logs, telemetry, experiments, and structured debugging methods.
Strong communication and collaboration skills across engineering, customer, and operations teams. Passion for building reliable next-generation AI infrastructure and solving complex system-level challenges at scale.
Experience with NVIDIA GPU systems, NVLink, NVSwitch, CUDA, and large-scale AI/HPC clusters such as NVIDIA GB200 NVL72.
Strong understanding of large-scale AI system architecture, including PCIe, memory hierarchy, DMA, high-speed interconnects, and distributed training/inference systems.
Experience with server management technologies, data center operations, cluster provisioning, scaling, and fleet monitoring.
Proven experience building diagnostics, automation, CI/CD pipelines, dashboards, and reliability tooling.

Nice-to-haves

Strong programming skills in C/C++ and Python; Bash/Shell scripting experience is a plus.

Application prep

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Keywords to mirror

aipythonci/cd

Platform: eightfold
Effort: medium

Benefits

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