Systems Performance Engineer - Kubernetes & AI Workloads

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

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.