Manager, Site Reliability Engineer - GeForce Now Cloud

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s motivated by outstanding 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. NVIDIA is at the forefront of generative AI models, from language to images. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIA, you’ll be immersed in a diverse, encouraging environment where everyone is inspired to do their best work.

We are looking for a Manager for Site Reliability Engineering to help build and lead its cloud service team for supporting, triaging, and building generative AI-powered visual applications. 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 solve a broad spectrum of problems. We live SRE practices that are key to product quality, such as limiting time spent on reactive operational work, blameless postmortems, proactive identification of potential outages, and iterative improvements, which all make for exciting wide-ranging day-to-day work. The person in this position will be growing a SRE team for Service Response and workflow and will drive tools/service development to maintain and improve service SLOs. We partner with Service Owners to drive the reliability of the service.

What you will be doing:

• Develop a team of SREs, providing mentorship, guidance, and support in achieving team goals.

• Nurture a culture of collaboration, innovation, and continuous improvement within the SRE team.

• Your team will be responsible for supporting and working on groundbreaking Generative AI inferencing workloads running in a globally distributed heterogeneous environment spanning 60+ edge locations plus all major cloud service providers. Ensure the best possible performance and availability on current and next-generation GPU architectures.

• Collaborate closely with the service owners, architecture, research, and tools teams at NVIDIA to achieve ideal results for AI problems at hand.

• Be a part of an on-call rotation while monitoring & supporting critical high-performance, large-scale services running multi-cloud.

• Communicating and reporting service KPIs, priorities, and issues to leadership while driving premier incident responses.

• Work closely with security teams to ensure the implementation of security best practices and compliance with relevant standards and regulations.

What we need to see:

• MS or PhD in an engineering or computer science-related field or equivalent experience

• 8+ overall years of experience operating & owning end-to-end availability and performance of critically meaningful services in a live-site production environment, either as an SRE or Service Owner.

• 6+ years of technical leadership beyond development that includes scoping, requirements gathering, leading, and influencing multiple teams of engineers on broad development initiatives.

• Experience leading an engineering team on projects with technical deep dives into cloud technologies (AWS/AZURE/GCP/OCI), code, networking, operating systems, storage etc.

• Solid understanding of containerization and microservices architecture, K8s. Excellent knowledge of the Kubernetes ecosystem and standard methodologies with K8s.

• Lead significant production activities, including change management, post-mortem reviews, workflow processes, software design, and delivering software automation in various languages (Python, or Golang) and technologies (CI/CD auto-remediation, alert correlation).

• Best in understanding SLO/SLIs, error budgeting, KPIs, and configuring for highly complex services.

Ways to stand out from the crowd:

• Exposure to containerization and cloud-based deployments for AI models.

• Excellent coding: Python, Go (Any similar language).

• Prior experience driving production issues and helping with on-call support.

• Understanding of Deep Learning / Machine Learning / AI.

• Experience with Cuda, PyTorch, TensorRT, TensorFlow, and/or Triton.

With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and versatile people in the world working with us and our engineering teams are growing fast in some of the most impactful fields of our generation: Deep Learning, Artificial Intelligence, and Autonomous Vehicles. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you.