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

NVIDIA AI; Seattle (WA); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equity

Health Insurance

Job summary

NVIDIA AI in Seattle is seeking a Lead performance and scalability analyst to optimize the Kubernetes-based accelerated runtime stack for large-scale AI workloads. You will collaborate with researchers and engineers to design automated workload tests and integrate performance testing into CI/CD pipelines.

The role focuses on performance, reliability, and scalability across GPU-accelerated platforms, requiring deep expertise in distributed systems and modern cloud-native tooling.

Qualifications

• Bachelor’s or Master’s degree in Engineering or equivalent experience.
• At least 8 years in computer architecture and distributed systems.
• Expertise in Kubernetes and experience with large-scale AI workloads are essential.

Responsibilities

• Lead performance and scalability analysis across the Kubernetes-based accelerated runtime stack.
• Collaborate with researchers and developers to design automated workload tests and integrate performance testing into CI/CD workflows.

Skills

Kubernetes

Distributed Systems

Containers

Systems Performance

Scalability

Golang

Python

AI Workloads

Cloud Platforms

Performance Optimization

Open-Source

GPU Operators

Device Plugins

Networking

Storage Systems

Benchmarking

Education

Bachelor’s or Master’s degree in Engineering or equivalent experience

Job description

Lead performance and scalability analysis across the Kubernetes-based accelerated runtime stack, focusing on NVIDIA components. Collaborate with researchers and developers to design automated workload tests and integrate performance testing into CI/CD workflows.

Requirements

Bachelor’s or Master’s degree in Engineering or equivalent experience, with at least 8 years in computer architecture and distributed systems. Expertise in Kubernetes and experience with large-scale AI workloads are essential.

Key Skills

• Kubernetes
• Distributed Systems
• Containers
• Systems Performance
• Scalability
• Golang
• Python
• AI Workloads
• Cloud Platforms
• Performance Optimization
• Open-Source
• GPU Operators
• Device Plugins
• Networking
• Storage Systems
• Benchmarking

Benefits

• Equity
• Health Insurance