Senior Site Reliability Engineer

Posted 3 Hours Ago
Be an Early Applicant
Hiring Remotely in CA, USA
Remote
168K-270K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Build and operate large-scale GPU cloud infrastructure through automation, self-healing systems, observability platforms, and infrastructure-as-code pipelines. Develop production-grade tools in Python or Go, manage Kubernetes and Linux environments, integrate data center and CI/CD systems, respond to incidents, and improve reliability through automation, monitoring, postmortems, and root-cause analysis.
Summary Generated by Built In

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.

Skills Required

  • 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
  • Experience designing, building, and owning production-quality tools and services
  • Deep knowledge of Kubernetes, Linux systems administration, and/or container technologies
  • Experience handling large-scale bare-metal and cloud infrastructure
  • Experience building data center automation tools for OS provisioning, image deployment, patching, packaging, and configuration management
  • Experience with CI/CD tooling and infrastructure-as-code workflows
  • Strong understanding of observability practices, including metrics, logging, distributed tracing, and alerting design
  • Excellent communication skills and ability to present technical work across multifunctional teams
  • Experience delivering automation or reliability platforms at large scale
  • Experience with DCIM systems and asset database design and implementation
  • Ability to debug and optimize code, reduce system-level toil, and drive measurable reliability improvements

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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