Senior Site Reliability Engineer

NVIDIA Corporation; United States; Remote; USD 168,000 - 270,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA leads in AI, HPC, and Accelerated Computing. Our GPU cloud infra powers the next generation of AI. We design, build, and maintain large-scale GPU infrastructure with automation for reliability and efficiency.

The Senior Site Reliability Engineer will build self-healing systems and IaC pipelines, monitor GPU/Kubernetes environments, and drive reliability improvements across thousands of machines. Equity and benefits are available.

Qualifications

• 6+ years of experience in SRE, production engineering, or infrastructure software engineering supporting large-scale, highly available environments.
• BS/BTech in Computer Science, Engineering, Physics, Mathematics, or equivalent experience.
• Strong software development skills with Python and/or Go; able to design, build, and own production-quality tools and services.
• Deep knowledge of Kubernetes, Linux systems administration, and/or container technologies; experience with large-scale bare-metal and cloud infrastructure.
• Experience building data center automation tools covering OS provisioning, image deployment, patching, packaging, and configuration management.
• Experience with CI/CD tooling and infrastructure-as-code workflows.
• Strong understanding of observability: metrics, logging, distributed tracing, and alerting design.
• Excellent communication skills with the ability to present technical work across multi-functional teams.

Responsibilities

• Design and build production-grade automation frameworks, workflows, and data models for provisioning, patching, image deployment, telemetry, and change management at large scale.
• Engage in the complete lifecycle of services from deployment to incident response and reliability improvements.
• Develop software tools and platforms that integrate across data center systems, including DCIM, observability stacks, control planes, and CI/CD pipelines.
• Monitor and operate large-scale GPU and Kubernetes environments; apply observability tooling to detect and resolve incidents.
• Build auto-healing systems by integrating incident analysis into automated break-fix and self-remediation solutions.
• Participate in on-call rotations and conduct blameless postmortems and root-cause-focused improvements.
• Scale systems through automation and self-service tooling to improve reliability and velocity.

Skills

Python

Go

Kubernetes

Linux

Observability

Education

BS/BTech in Computer Science, Engineering, Physics, Mathematics, or equivalent

Tools

CI/CD tooling

Infrastructure as Code

DCIM

Job description

NVIDIA is seeking a Senior Site Reliability Engineer who combines an SRE’s reliability approach with strong software build and development skills. Our Production Engineering team blends software and systems engineering to design, build, and maintain large-scale GPU cloud infrastructure with exceptional efficiency and availability. We believe outstanding software is the foundation of operating production at scale, keeping services reliable and enabling developers to deploy changes authoritatively. In this role, you will reduce manual toil by building automation frameworks, self-healing systems, observability platforms, and infrastructure-as-code pipelines that support thousands of machines. You will be responsible for the full lifecycle of your work, from architecture and development through deployment, operations, and continuous improvement. If you are passionate about special GPU infrastructure and the software that powers it, this role offers the opportunity to shape both.

What you'll be doing:

• Design and build production-grade automation frameworks, workflows, and data models that reduce manual operational work across provisioning, patching, image deployment, telemetry, and change management at large scale.
• Engage in the complete lifecycle of services from deployment to incident response and long-term reliability improvement.
• Develop software tools and platforms that integrate across data center systems: DCIM, alerting and observability stacks, compute/storage/networking control planes, and CI/CD pipelines.
• Monitor and handle large-scale GPU and Kubernetes production environments; apply advanced observability tooling (Grafana, OpenTelemetry, PagerDuty) to proactively detect, prevent, and resolve incidents.
• Build predictive and auto-healing systems by integrating incident analysis insights into automated break-fix and self-remediation solutions.
• Participate in on-call rotations and practice sustainable incident response, including blameless postmortems and systematic root-cause-focused improvements.
• Scale systems sustainably through code by pushing automation and self-service tools that improve reliability and engineering velocity.

What we need to see:

• 6+ years of experience in SRE, production engineering, or infrastructure software engineering supporting large-scale, highly available environments.
• BS/BTech in Computer Science, Engineering, Physics, Mathematics, or equivalent experience.
• Strong software development skills with expertise in Python and/or Go; ability to design, build, and own production-quality tools and services, not just scripts.
• Deep knowledge of Kubernetes, Linux systems administration, and/or container technologies; experience handling large-scale bare-metal and cloud infrastructure.
• Confirmed experience building data center automation tools covering OS provisioning, image deployment, patching, packaging, and configuration management.
• Experience with CI/CD tooling and infrastructure-as-code workflows.
• Strong understanding of observability practices: metrics, logging, distributed tracing, and alerting design.
• Excellent communication skills with the ability to present technical work persuasively across multi-functional teams.

Ways to stand out from the crowd:

• Built and delivered automation or reliability platforms at large scale. You measure impact by machines handled, incidents prevented, or hours of toil eliminated.
• You address production problems as an application developer would a build: consider the architecture initially, automate fully, and improve the system before moving on.
• You have a strong passion for investing in groundbreaking technology and environments where you learn new systems quickly.
• Confirmed ability to debug and optimize code, reduce system-level toil, and drive measurable reliability improvements through software.
• Experience with DCIM systems and asset database design and implementation.

NVIDIA leads in Artificial Intelligence, High-Performance Computing, and Accelerated Computing. Our invention, the GPU, powers the next generation of AI infrastructure. We build systems to run this infrastructure globally. We need engineers to write software that keeps it reliable, efficient, and improving. If this work excites you, we want to hear from you.

Known throughout the technology industry as a leading employer, NVIDIA delivers highly competitive salaries and an extensive benefits package. As you consider your future, explore what we can provide for you and those closest to you at www.nvidiabenefits.com/

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 270,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until October 31, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.