Capacity Operations Manager

Capacity Operations Manager (Finance)

Our technology has no boundaries! NVIDIA is building the world's most groundbreaking and pioneering computing platforms. Because of our work, scientists, researchers, and engineers can advance their ideas. At its core, our visual computing technology not only enables an outstanding computing experience but it is also energy efficient! We pioneered a supercharged form of computing loved by the most fast‑paced computer users in the world – scientists, designers, artists, and gamers.

It is not just technology, though! It is our people, some of the brightest in the world, and our company makes NVIDIA one of the most fun, innovative, and dynamic places to work. At the center of NVIDIA are our core values, like innovation, excellence, determination, and team, that guide us to be the best we can be.

• Orchestrate the build out of High Performance Computing (HPC) clusters working closely with internal and external engineering teams.
• Manage and optimize GPU capacity and other compute resources across various cloud service providers to meet growing demands and ensure efficient utilization.
• Build, develop, and maintain data models, reporting systems, data automation systems, dashboards, and performance metrics that support NVIDIA Infrastructure governance programs and strategic capacity decisions.
• Analyze the technical and business needs for GPU capacity and other compute resources from various internal and external teams.
• Identify performance bottlenecks in day‑to‑day usage of compute resources and collaborate with relevant infrastructure teams to resolve them.
• Drive infrastructure resource efficiency initiatives in partnership with engineering, finance, and product teams.
• Develop and enhance tooling for our cloud infrastructure and analytics platform to optimize resource usage and performance for NVIDIA and its customers. This includes crafting and developing tools for automating workflows and potentially leveraging AI techniques to extract useful signals and insights from generated data.
• Partner and cross‑collaborate with Finance, Product, Service Owners, and Infrastructure Engineering teams to align cloud capacity management with company goals and develop Infrastructure and Service Level Key Performance Indicators (KPIs) to match Customer satisfaction.
• Lead multi‑year budget‑based compute resource planning with finance, procurement and engineering.

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, or equivalent experience.
• 5+ years of overall experience in cloud computing, specifically in managing or utilizing GPU capacity for high performance computing. A proven track record of large‑scale computing operations and planning is a plus.
• Strong technical proficiency in cloud architecture, development and deployment, and managing large data sets. Experience with command line interfaces and shell scripting languages.
• Deep understanding of cloud service models (IaaS, PaaS, SaaS) and cloud infrastructure technologies. Hands‑on experience with Cloud Service Providers such as AWS, Azure, GCP, and OCI is required.
• Demonstrated experience in leveraging AI tools and techniques to extract useful signals and insights from data, specifically to improve resource usage and automation.
• Strong understanding and practical application of statistical modeling and machine learning methodologies for improving operational efficiency and informing strategic capacity decisions.
• Knowledge of analytics, statistical modeling, and machine learning methodologies.
• Excellent communication and interpersonal skills, with the ability to collaborate effectively with various departments and influence strategic decisions.
• Naturally curious, accountable, and responsible.
• Ability to operate effectively amidst uncertainty and rapidly changing business conditions, with an agile mindset and a commitment to ongoing improvement.

NVIDIA is leading 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…