Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale

What you'll do

• 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 for hyperscale cluster operation.
• Improve container startup and cold-start latency to enable low-latency inference scaling across thousands of GPU nodes.
• Assess and contribute to open-source projects that optimize Kubernetes for AI workloads.
• Advance the scalability and performance of confidential containers for encrypted inference workloads.
• Use large-scale simulation infrastructure to model AI-factory deployments and validate scalability across thousands of simulated GPUs.
• Design automated workload tests and integrate continuous performance testing into modern CI/CD workflows.
• Document technical findings and present results at internal meetings and industry events like KubeCon.

What we're looking for

• Bachelor’s or Master’s degree in Engineering or equivalent experience, ideally in Electrical, Computer Engineering, or Computer Science.
• 8+ years of experience in computer architecture, networking, storage systems, and accelerator-based platforms.
• Expertise in Kubernetes and familiarity with the broader CNCF ecosystem.
• Deep experience with large-scale, parallel, distributed accelerator systems and performance optimization of AI workloads.
• Experience with performance modeling and benchmarking for large-scale systems.
• Proficiency in Golang and/or Python.
• Strong familiarity with the NVIDIA software stack across training and inference.
• Expertise with at least one major public cloud provider (e.g., AWS, Azure, GCP, or OCI).
• Strong operational experience with any one of the Kubernetes distributions (preferred).
• Prior experience scaling Kubernetes clusters to ultra-large node and object counts (preferred).
• Demonstrated history of working in the open-source community (preferred).
• Excellent communication and interpersonal abilities (preferred).
• PhD or equivalent experience in relevant areas (preferred).