Distinguished Site Reliability Engineer - Cloud

2100 NVIDIA USA; United States; On-site; USD 320,000 - 488,750; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a Site Reliability Engineer to design, build, and maintain large-scale production systems with high reliability and availability.

The role focuses on automation, performance tuning, and proactive improvements across Kubernetes clusters, cloud tools, and monitoring systems. Collaboration, ownership, and a blameless culture drive ongoing reliability and efficiency.

Qualifications

• BS degree in Computer Science or a related technical field or equivalent experience.
• 16+ years of experience with infrastructure automation and distributed systems design.
• Experience with design and development of tools for running large-scale private or public cloud systems in production.
• Proficiency in one or more of Python, Go, Perl or Ruby; strong Linux, networking and container knowledge.

Responsibilities

• Lead, design, implement and support operational and reliability aspects of large-scale Kubernetes clusters.
• Engage in the full lifecycle of services from design through deployment and refinement.
• Provide system design consulting, develop tools, manage capacity and conduct launch reviews.
• Monitor availability, latency and overall health of services in production.
• Scale systems with automation and drive changes to improve reliability and velocity.
• Perform incident response with blameless postmortems.
• Participate in on-call rotations to support production systems.

Skills

Infrastructure automation

Distributed systems

Cloud tooling

Python

Go

Linux

Networking

Containers

Education

BS in Computer Science or related field

Tools

Kubernetes

OpenStack

Docker

Ruby

Job description

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 demand knowledge across different systems, networking, coding, database, capacity management, continuous delivery and deployment and open source cloud enabling technologies like Kubernetes and OpenStack. 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 enabling 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.

As SREs are responsible for the big picture of how our systems relate to each other, we use a breadth of tools and approaches to tackle a broad spectrum of problems. Practices such as limiting time spent on reactive operational work, blameless postmortems and proactive identification of potential outages factor into iterative improvement that is key to both product quality and interesting dynamic day-to-day work. SRE's culture of diversity, intellectual curiosity, problem solving and openness is important to our success. Our organization brings together people with a wide variety of backgrounds, experiences and perspectives. We encourage them to collaborate, think big and take risks in a blame-free environment. We promote self-direction to work on meaningful projects, while we also strive to build an environment that provides the support and mentorship needed to learn and grow.

What you’ll be doing

• 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 postmortems
• Be part of an on call rotation to support production systems

What we need to see

• 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, experience with design, develop tools for running large scale private or public cloud system in Production
• Experience in one or more of the following: Python, Go, Perl or Ruby
• In depth knowledge on Linux, Networking and Containers

Ways to stand out from the crowd

• 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, OpenStack 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.

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.