About the position
Azure Compute is one of Microsoft Azure’s most profitable and rapidly growing services. It provides millions of virtual machines that enable customers to run their workloads in the cloud. As a globally available foundational service, Azure Compute supports the scale of services such as Bing, Skype, Azure Store, and Structured Query Language (SQL) databases. It also powers millions of multiplayer gaming sessions and enables the resolution of large computational problems in seconds. The Azure Compute team serves as the core of Microsoft’s cloud operating system. The team builds fault-tolerant distributed systems on top of standard datacenter hardware to deliver infrastructure for hosting cloud applications in virtual servers. This work creates the perception of limitless, elastic, and always-available resources for customers. As a Senior Software Engineer on this team, you will be a key member of the Azure Kronox team. You will work with a team of engineers building and growing a product partnering with our customers and partners and providing greater intelligence and choices to customers when accessing the Azure capacity across regions. Kronox is a team within Azure Compute that helps customers manage virtual machines at scale. It provides a streamlined way to schedule the setup and teardown of resources, optimizing cost of goods sold (COGS). The team continuously balances tradeoffs between maintaining a high service level agreement (SLA)—ensuring resources are available when needed—and minimizing COGS by avoiding unnecessary resource usage. This work places Kronox at the intersection of large-scale distributed systems and advanced data science, including machine learning (ML) prediction models.
Responsibilities
- Build and grow products in partnership with customers and partners.
- Provide greater intelligence and choices to customers accessing Azure capacity across regions.
- Manage virtual machines at scale.
- Schedule the setup and teardown of resources to optimize cost of goods sold (COGS).
- Balance tradeoffs between maintaining a high service level agreement (SLA) and minimizing COGS.
- Work at the intersection of large-scale distributed systems and advanced data science.
