Distinguished Site Reliability Engineer - Cloud

Site Reliability Engineering (SRE) at NVIDIA is an engineering discipline to design, build and maintain large scale production systems with high efficiency and availability using the combination of software and systems engineering practices. This is a highly specialized discipline which demands knowledge across different systems, networking, coding, database, capacity management, continuous delivery and deployment and open source cloud enabling technologies like Kubernetes and Open Stack.

SRE at NVIDIA ensures that our internal and external facing GPU cloud services run maximum reliability and uptime as promised to the users and at the same time enables developers to make changes to the existing system through careful preparation and planning while keeping an eye on capacity, latency and performance. SRE is also a mindset and a set of engineering approaches to running better production systems and optimizations.

Much of our software development focuses on eliminating manual work through automation, performance tuning and growing efficiency of production systems.

• Lead, design, implement and support operational and reliability aspects of large‑scale Kubernetes clusters with focus on performance at scale, real‑time monitoring, logging and alerting
• Engage in and improve the whole lifecycle of services—from inception and design through deployment, operation and refinement
• Support services before they go live through activities such as system design consulting, developing software tools, platforms and frameworks, capacity management and launch reviews
• Maintain services once they are live by measuring and monitoring availability, latency and overall system health
• Scale systems sustainably through mechanisms like automation, and evolve systems by pushing for changes that improve reliability and velocity
• Practice sustainable incident response and blameless post‑mortems
• Be part of an on‑call rotation to support production systems

• BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics), or equivalent experience
• 16+ years of experience with infrastructure automation, distributed systems design, and experience designing and developing tools for running large‑scale private or public cloud systems in production
• Experience in one or more of the following:
  Python, Go, Perl or Ruby
• In‑depth knowledge of Linux, networking and containers

• Interest in crafting, analyzing and fixing large‑scale distributed systems
• Systematic problem‑solving approach, coupled with strong communication skills and a sense of ownership and drive
• Ability to debug and optimize code and automate routine tasks
• Experience in using or running large private and public cloud systems based on Kubernetes, Open Stack and Docker

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 320,000 USD - 488,750 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until May 8, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

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