NVIDIA
CapacityOperationsandAnalyticsManager
Neural analysis suggests this role is
optimal for Senior candidates.
“Capacity Operations and Analytics Manager at NVIDIA. Skills: GPU capacity management, compute resource optimization, data modeling, performance metrics, resource planning, continuous improvement, cloud infrastructure analytics, statistical modeling, machine learning methodologies. 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,”
What You'll Achieve.
meet growing demands; ensure efficient utilization; support NVIDIA Infrastructure governance programs; support strategic capacity decisions; resolve performance bottlenecks; drive infrastructure resource efficiency initiatives; optimize resource usage and performance for NVIDIA and its customers; align cloud capacity management with company goals; develop Infrastructure and Service Level Key Performance Indicators (KPIs) to match Customer satisfaction
Industry & Context.
Identify performance bottlenecks in day-to-day usage of compute resources; resolve performance bottlenecks; extract useful signals and insights from generated data
What They're Looking For.
Must Have
10+ years of overall experience in cloud computing, specifically in managing or sourcing GPU capacity with cloud service providers, technical proficiency in cloud architecture, development and deployment, and managing large data sets, Deep understanding of cloud service models (IaaS, PaaS, SaaS) and cloud infrastructure technologies, 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, understanding and practical application of statistical modeling and machine learning methodologies for improving operational efficiency and informing strategic capacity decisions, Proficiency with data analytics, visualization, and monitoring tools such as Kibana, Grafana, Splunk, Prometheus, Tableau, Plotly, 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, Ability to operate effectively amidst uncertainty and rapidly changing business conditions, with an agile mindset and a commitment to ongoing improvement
Nice to Have
A proven track record of large-scale computing operations and planning is a plus
What You'll Do.
Manage and optimize GPU capacity and other compute resources across various cloud service providers to meet growing demands and ensure efficient utilization
and maintain data models
data automation systems
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
Develop and enhance tooling for our cloud infrastructure and analytics platform to optimize resource usage and performance for NVIDIA and its customers
Lead multi-year budget-based compute resource planning with engineering
How You'll Work.
Team & Collaboration
Collaborate with relevant infrastructure teams to resolve performance bottlenecks; Partner and cross-collaborate with Finance, Product, Service Owners, and Infrastructure Engineering teams to align cloud capacity management with company goals; Collaborate effectively with various departments and influence strategic decisions
Communication Scope
Excellent communication and interpersonal skills; ability to collaborate effectively with various departments and influence strategic decisions
Process & Methodology
multi-year budget-based compute resource planning
Full Job Description
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’s 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. **What you will be doing:** * 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 Infras
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