Software Engineer - Capacity Optimization

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.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

• Design new tools and processes to enable better data modeling, analysis, and experimentation for capacity across Azure.
• Understand platform capacity constraints and work with teams across Azure to improve capacity manageability and efficiency.
• Build models, simulations, scalable and automated analytical systems and data mining frameworks to derive profound insights into the Azure Compute platform and its efficiency and capacity.
• Drive improvements to the product design and architecture, leading to increased customer satisfaction.
• Lead and collaborate with experts from across the company to advance capacity management, capacity planning, and efficiency.
• Contribute to the team culture and apply best practices in your day to day work.

Qualifications

• BS in Computer Science or equivalent  
• 2+ years of software development hands-on industry experience working on cloud infrastructure-related problems, with impact on critical product and business decisions.  
• Azure Cloud Services development experience, or related. 
• Programming skills (esp. related to data technologies like Python, PERL, Java, C#, etc.), and proficiency with relational databases (Kusto, SQL or similar).   
• Good understanding of a modern state-of-the-art cloud platform, and related technologies.   
• A proven track record of collaborating across organizational boundaries and delivering great results.  
• Comfortable to work across the boundary between data science and software engineering. 
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Additional or Preferred Qualifications (PQs):

• Master's Degree in Computer Science or related field. 
• 1+ years software development experience or equivalent experience. 
• Experience with Globally Distributed cloud systems with focus on quality and scalability. 
• Experience with working across data science and software development boundary. 
  
  

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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