Senior Systems Software Engineer, Accelerated Kubernetes Performance and Scale - DGX Cloud

What you'll do

• Analyze and improve performance and scalability across Kubernetes control and data planes, including NVIDIA components and container startup.
• Design and contribute upstream changes and open-source projects to support reliable AI workloads at hyperscale.
• Build simulations, workload tests, monitoring, and CI/CD performance testing; document findings and engage with research, customers, and upstream communities.

What they ask for

• 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 distributed accelerator systems; experience optimizing AI workload performance and conducting large-scale performance modeling and benchmarking.
• Proficiency in Golang and/or Python; familiarity with the NVIDIA software stack and expertise with at least one major public cloud provider.

Nice to have

• Operational experience with a Kubernetes distribution or experience scaling clusters to ultra-large node and object counts.
• Open-source community experience; PhD or equivalent experience in relevant areas.

Pay

184,000 USD - 287,500 USD (base salary, Level 4); 224,000 USD - 356,500 USD (base salary, Level 5)

Tools

Kubernetes, Golang, Python, GPU Operator, Network Operator, DSX, Grove, gateway-api-inference-extension

AI focus

Scales AI infrastructure and workloads, including inference and confidential inference; uses large-scale simulations and production agent traces to test AI-factory deployments and reduce cost per token.