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Senior Site Reliability Engineer

NVIDIA

Remote · USFull-time$168–270K/yrSeen 6 days agoSeen in employer's feed 1 day ago

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At a glance

Compensation
$168–270K/yr
Location
Remote · US
Schedule
Full-time
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

NVIDIA seeks a Senior Site Reliability Engineer for its Production Engineering team, combining reliability practices with software development to operate large-scale GPU cloud infrastructure. The role spans architecture, development, deployment, operations, and continuous improvement. The engineer will build automation, self-healing systems, observability platforms, and infrastructure-as-code pipelines to reduce toil and support reliable services at scale.

Skills & qualifications

RequiredNice to have

Skills

PythonGoKubernetesLinux Systems AdministrationContainer TechnologiesBare-Metal InfrastructureCloud InfrastructureData Center AutomationOS ProvisioningImage DeploymentPatchingPackagingConfiguration ManagementCI/CDInfrastructure as CodeObservabilityMetricsLoggingDistributed TracingAlerting DesignCommunicationTechnical PresentationAutomation PlatformsReliability PlatformsArchitectureDebuggingCode OptimizationDCIM SystemsAsset Database DesignAsset Database Implementation

Qualifications

6+ Years SRE or Infrastructure ExperienceBS/BTech in Computer Science or Related Fields or Equivalent Experience

Full job description

US, CA, Remote

Full time

JR2028236

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 other objective job-related factors. The expected base salary range for this position is 168,000 USD – 270,250 USD.

You will also be eligible for equity and benefits (https://www.nvidia.com/en-us/benefits/) .

Applications for this job will be accepted at least until November 3, 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.

NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry.

Learn more about NVIDIA .

How this job compares

Set against the 2,376 open Site Reliability Engineer jobs on Olive Jobs, counted November 3, 2026.

Pay
  • This posting$168–270K/yr
  • California median$165–244K/yr387 salary ranges
  • US median$136–228K/yr1,974 salary ranges

This range's midpoint, $219K, is 7% above the California median midpoint ($206K) — in the middle half of Site Reliability Engineer salary ranges in California.

Openings
Olive Jobs lists 462 open Site Reliability Engineer jobs in California and 2,376 across the US. 20% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 6 years of experience; Site Reliability Engineer postings that state a minimum ask for 5 years at the median (1,975 postings).
Education
688 of the 2,376 open Site Reliability Engineer jobs (29%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 3, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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