Senior Kubernetes Performance Engineer for AI Scale

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 184.000 - 357.000; Vollzeit

Benefits dieser Stelle

Equity

Zusammenfassung

NVIDIA is hiring for a senior engineering role focused on Kubernetes-based AI workloads. You will analyze performance, design architectural changes, and improve startup latency across large GPU clusters.

Collaboration with researchers, developers, and upstream communities will be key, along with contributing to open-source projects and ensuring scalable, secure AI deployments. You’ll work with the NVIDIA software stack for training and inference, across cloud providers, in a hybrid-remote setup,

Qualifikationen

• Bachelor’s or Master’s degree in Engineering or equivalent experience.
• 8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms.
• Expertise in Kubernetes and familiarity with the broader CNCF ecosystem.

Aufgaben

• Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack.
• Design and contribute upstream architectural changes to the Kubernetes control plane and related projects.
• Improve container startup and latency for AI workloads on Kubernetes across thousands of GPU nodes.
• Contribute to open-source projects like Grove and gateway-api-inference-extension for scalable AI workloads.
• Advance scalability and performance of confidential containers (CoCo) on Kubernetes.

Kenntnisse

Kubernetes expertise

Golang

Python

Cloud services (AWS/Azure/GCP)

Ausbildung

Bachelor’s or Master’s in Engineering

Tools

Kubernetes

Jobbeschreibung

NVIDIA is hiring for a senior engineering role focused on Kubernetes-based AI workloads. You will analyze performance, design architectural changes, and improve startup latency across large GPU clusters.

Collaboration with researchers, developers, and upstream communities will be key, along with contributing to open-source projects and ensuring scalable, secure AI deployments. You’ll work with the NVIDIA software stack for training and inference, across cloud providers, in a hybrid-remote setup,