Senior AI Infra Systems Engineer (Kubernetes & Distributed)

NVIDIA Corporation; United States; Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

NVIDIA is seeking a Senior Systems Software Engineer to help scale AI infrastructure on Kubernetes for DGX Cloud workloads. You will own performance and scalability across GPU operators, containers, and distributed AI services, shaping production-grade infrastructure with focus on efficiency and cost.

You will collaborate with researchers and upstream communities, improve startup latency, and contribute to open-source projects while engaging with the broader CNCF ecosystem.

Qualifications

• 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 (AWS, Azure, GCP, or OCI)

Responsibilities

• Lead end-to-end performance and scalability analysis across the Kubernetes-based accelerated runtime stack, including NVIDIA components.
• Design and contribute upstream architectural changes to the Kubernetes control plane and related projects for hyperscale clusters.
• Improve container startup and cold-start latency for GPU nodes to enable scalable AI workloads on Kubernetes.
• Assess, improve, and contribute to open-source projects for Kubernetes AI workloads (e.g., Grove and gateway-api-inference-extension).
• Advance scalability and performance of confidential containers (CoCo) on Kubernetes for encrypted inference workloads in production.
• Model AI-factory deployments using DSX and simulation infra to validate scalability across thousands of GPUs.
• Collaborate with researchers, developers, customers, and upstream communities to design tests and CI/CD integrations.
• Document methods and present findings at internal and industry events; engage with Kubernetes SIG Scalability and CNCF.

Skills

Kubernetes

Distributed systems

Performance optimization

Golang

Python

NVIDIA software stack

Cloud platforms (AWS/Azure/GCP/OCI)

Education

Bachelor's degree in Engineering

Master's degree in Engineering

Tools

GPU Operator

Network Operator

node-feature-discovery

topograph

dra-driver-nvidia-gpu

nvsentinel

Job description

NVIDIA is seeking a Senior Systems Software Engineer to help scale AI infrastructure on Kubernetes for DGX Cloud workloads. You will own performance and scalability across GPU operators, containers, and distributed AI services, shaping production-grade infrastructure with focus on efficiency and cost.

You will collaborate with researchers and upstream communities, improve startup latency, and contribute to open-source projects while engaging with the broader CNCF ecosystem.