Senior Systems Automation Engineer, Large-Scale Infra

NVIDIA Corporation; Durham (NC); On-site; USD 190,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Systems & Software Engineer to design, build, and run reliable large-scale infrastructure platform services. You will create automation to scale operations and support an observability-driven lifecycle in a high-performance environment.

You will work with Python/Go, Linux, containers, Kubernetes, and cloud technologies to improve production systems and drive robust solutions across NVIDIA GPUs and data centers.

Qualifications

• BS degree in Computer Science or a related technical field involving coding
• Experience coding in Python and/or Go (able to produce code without AI during interview)
• Experience with infrastructure automation and distributed systems design
• Experience developing tools for large-scale private or public cloud systems in production
• In-depth knowledge of Linux systems and Containers
• 8+ years of relevant experience

Responsibilities

• Design, build, deploy, and run infrastructure services & manage the software life cycle to meet business goals
• Build and maintain automation to eliminate manual toil and scale output without increasing effort
• Define internal service level objectives and error budgets as part of observability strategy
• Practice blameless incident prevention and incident response while on-call
• Consult with peer teams on systems design best practices

Skills

Python

Go

Distributed systems

Infrastructure automation

Linux

Containers

Kubernetes

OpenStack

Docker

Multi-cloud

Slurm

Education

Bachelor's degree in CS or related field

Tools

Slurm

CI/CD pipelines

Job description

NVIDIA is seeking a Systems & Software Engineer to design, build, and run reliable large-scale infrastructure platform services. You will create automation to scale operations and support an observability-driven lifecycle in a high-performance environment.

You will work with Python/Go, Linux, containers, Kubernetes, and cloud technologies to improve production systems and drive robust solutions across NVIDIA GPUs and data centers.