Site Reliability Engineer

Role Overview

NVIDIA is hiring a Site Reliability Engineer to support the systems behind its AI-powered enterprise products. You'll work alongside Cloud, Platform, Security, and AI/ML teams on everything from database automation to observability, while picking up modern SRE and AI-assisted engineering practices along the way.

What You'll Do

• Support SRE initiatives that improve reliability, scalability, and developer efficiency
• Help build and maintain distributed systems behind AI-powered enterprise products
• Automate database operations — provisioning, scaling, backup, and failover
• Build dashboards, alerts, and automation scripts to strengthen observability
• Take part in incident response: triage, troubleshooting, resolution, and post-incident reviews
• Collaborate with Cloud, Platform, Security, and AI/ML teams on platform reliability
• Operate and troubleshoot Kubernetes-based, cloud-native infrastructure
• Use AI-assisted engineering tools — coding agents and LLM-powered tooling — in daily workflows

What We're Looking For

• Bachelor's degree in Computer Science or a related technical field (or equivalent practical experience)
• Foundational proficiency in at least one language such as Python, TypeScript, JavaScript, or Go
• Basic understanding of a cloud platform (AWS, Azure, or GCP) and containerization (Docker, Kubernetes)
• Familiarity with Linux/Unix systems, networking fundamentals, and Git
• Basic knowledge of relational databases (PostgreSQL/MySQL), including SQL and indexing
• Strong problem-solving instincts and comfort working in a fast-paced, collaborative team

Nice to Have

• Project, internship, or coursework experience with cloud infrastructure, automation, or DevOps/SRE practices
• Open-source contributions or participation in hackathons/coding competitions
• Exposure to AI/ML — building basic models, using LLM APIs, or AI-powered dev tools like Copilot or Cursor
• Hands-on experience with CI/CD pipelines or container orchestration

About NVIDIA

NVIDIA, founded in 1993, pioneered accelerated computing and the GPU. It has since grown into a full-stack computing company whose data-center-scale platforms power much of the modern AI industry.