Azure is Microsoft’s central cloud infrastructure hosting both our public cloud offerings as well as a vast number of Microsoft-internal cloud scale services. Cloud computing is a highly competitive and rapidly growing market, and it is Azure’s aim to be an industry leader in all relevant aspects and dimensions across its platform and services. Within Azure, the Azure Compute team is the core infrastructure team responsible for hosting virtual machines (VMs), containers, and other workloads.

One of the fundamental core disciplines in cloud computing is capacity management. Capacity management needs to ensure that on the one hand, there is sufficient capacity across all regions, allocation domains, and hardware infrastructure to meet all customer demand; while on the other hand ensuring that capacity is provisioned efficiently thereby avoiding overspending and cost of goods sold (COGS) and capital expenditures (CAPEX) impact. At the scale of Azure’s business, managing this trade-off across the entire Azure Compute fleet is an enormously complex and challenging task, where improvements can make the difference between customer allocation failures on the one hand, and gargantuan savings on the other.

The Azure Compute Capacity and Efficiency (AC2E) team is the team in Azure Compute tasked with managing all aspects of capacity and efficiency management across the fleet. Our primary task is to provide a fully automated and highly optimized tracking and management system. This system – of which CMAS (Capacity Management Automation System) is a core piece – uses numerous state-of-the-art algorithms. We use artificial intelligence to automatically predict capacity risk and execute the correct mitigation actions directly into the Azure Compute platform. As a member of our team, you will work closely with our engineers, program managers, and data scientists across the different platform teams within Azure Compute as well as our partners in capacity planning. You will formulate the business problems, and drive solutions end-to-end from design to production. You will also be involved in strategic decision making within Azure Compute for all feature work that impacts capacity and efficiency.

The value of your work will be reflected as improvements to the Azure platform, Azure service capacity fulfillment rate, customer satisfaction, and various efficiency metrics, including COGS reduction. Our team is a balanced team of data science and development engineers, and we work very closely with our partners in the program management team. We heavily engage in using state-of-the-art data science/applied statistical techniques like anomaly detection, machine learning, and experimentation methodologies, and if you are interested in such techniques and their applications to highly-complex real-world problems, you will fit right into our team. Collectively, we deliver world-class innovation.

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