Senior Site Reliability Engineer, AI Infrastructure

Joining NVIDIA's AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of AI workloads, as well as developing scalable AI and Data infrastructure tools and services. Our objective is to deliver a stable, scalable environment for AI researchers, providing them with the necessary resources and scale to foster innovation. We are seeking a Senior Site Reliability Engineer (SRE) to join our team. You'll be instrumental in designing, building, and maintaining cloud services that enable large-scale AI training and inferencing. The responsibilities include implementing software and systems engineering practices to ensure high efficiency and availability of the platform, as well as applying SRE principles to improve production systems and optimize service SLOs. Additionally, collaboration with our customers to plan implement changes to the existing system, while monitoring capacity, latency, and performance is part of the role.

As a Senior SRE at NVIDIA, you will have the opportunity to work on innovative technologies that power the future of AI and data science, and be part of a dynamic and supportive team that values learning and growth. The role provides the autonomy to work on meaningful projects with the support and mentorship needed to succeed, and contributes to a culture of blameless postmortems, iterative improvement, and risk-taking. If you are seeking an exciting and rewarding career that makes a difference, we invite you to apply now!

What you'll be doing:

• Develop software solutions to ensure reliability and operability of large-scale systems supporting machine-critical use cases.
• Gain a deep understanding of our system operations, scalability, interactions, and failures to identify improvement opportunities and risks.
• Create tools and automation to reduce operational overhead and eliminate manual tasks.
• Establish frameworks, processes, and standard methodologies to enhance operational maturity, team efficiency, and accelerate innovation.
• Define meaningful and actionable reliability metrics to track and improve system and service reliability.
• Oversee capacity and performance management to facilitate infrastructure scaling across public and private clouds globally.
• Build tools to improve our service observability for faster issue resolution.
• Practice sustainable incident response and blameless postmortems
• Skilled in problem-solving, root cause analysis, and optimization.

What we need to see:

• Minimum of 6 years of experience in SRE, Cloud platforms, or DevOps with large-scale microservices in production environments.
• Bachelor's degree or equivalent experience.
• Strong understanding of SRE principles, including error budgets, SLOs, and SLAs.
• Experience with AI training and inferencing and data infrastructure services.
• Expertise in building and operating large-scale observability platforms for monitoring and logging (e.g., ELK, Prometheus, Loki).
• Proficiency in programming languages such as Python, Go, Perl, or Ruby.
• Hands-on experience with scaling distributed systems in public, private, or hybrid cloud environments.
• Experience in deploying, supporting, and supervising services, platforms, and application stacks.
• Knowledge of CI/CD systems, such as GitLab and Familiarity with Infrastructure as Code (IaC) methodologies and tools.
• Excellent communication and collaboration skills, and a culture of diversity, intellectual curiosity, problem solving, and openness are essential.

Ways to stand out from the crowd:

• Good understanding on DL frameworks, orchestrators like PyTorch, TensorFlow, JAX, and Ray
• Strong background in software design and development.
• Experience operating large-scale distributed systems with strong SLAs.
• Extensive experience in operating data platforms.
• Proficiency in incident, change, and problem management processes.

NVIDIA leads the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing, and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions, from artificial intelligence to autonomous cars. NVIDIA is looking for exceptional people like you to help us accelerate the next wave of artificial intelligence.

The base salary range is 164,000 USD - 327,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.