Site Reliability Engineer
NVIDIA
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people.
Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
What you'll be doing:
- Support and contribute to SRE initiatives that improve reliability, scalability, and developer efficiency across enterprise systems.
- Assist in building and maintaining distributed systems that power NVIDIA’s AI-powered enterprise products and services, learning modern architectural patterns along the way.
- Help automate database operations — including provisioning, scaling, backup, and failover — for relational and vector database services.
- Contribute to observability and monitoring efforts by building dashboards, alerts, and automation scripts to improve system performance and reliability.
- Participate in incident response processes, learning to triage issues, reduce mean time to resolution (MTTR), and contribute to post-incident reviews.
- Collaborate with Cloud, Platform, Security, and AI/ML teams to support platform reliability and help implement SRE best practices.
- Learn to operate and troubleshoot complex systems — including Kubernetes-based and cloud-native infrastructure — following established standards in system design and incident management.
- Explore and adopt AI-assisted engineering practices, including coding agents and LLM-powered tooling, to accelerate day-to-day development workflows.
What we need to see:
- BS degree in Computer Science or a related technical field (e.g., physics, mathematics), or equivalent practical experience.
- Foundational proficiency in at least one programming language such as Python, TypeScript, JavaScript, or Go.
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