Principal Supercomputing Software Engineer

Microsoft Azure Artificial Intelligence/High Performance Computing (AI/HPC) team is looking for systems engineers, architects and thought leaders to enable customers in deploying, monitoring, profiling, and debugging their applications on hyperscale cloud infrastructure. Azure is enabling the largest supercomputing deployments to tackle complex computational problems in public cloud, evident from the various HPC products that have already made the mark on Top500, MLPerf and Graph500 rankings.

At this supercomputing scale, we need specialized tools and techniques to maintain the reliability, runtime performance, health of the system and running jobs continuing to meet the Service Level Agreements (SLAs) of customers. Your job would be to build and use state-of-the-art tools and techniques, find operational gaps and instrument features to achieve the smooth operation of cloud-native supercomputers. As a Principal Supercomputing Engineer, you would also bring to the table establishing best practices drive architectural changes and influence roadmap of relevant software and hardware components. Your work will directly impact business goals of a wide range of users and facilitate the next wave of growth and innovation in AI, and HPC in the cloud in general.



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.

Qualifications

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical or scientific field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience
• 5+ years of experience in operating AI/HPC systems, developing and running AI/HPC applications on clusters, or operating Cloud Infrastructure
• 3+ years of specialized experience with one of AI/HPC system management OR High-Speed Networks OR HPC Storage OR managing Cloud Infrastructure

Other Requirements:

• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: 
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications: 

• Masters' Degree or PhD in Computer Science or related technical or scientific field
• Operational experience running large scale HPC systems or infrastructure situated in Cloud environments
• Previous experience with running and troubleshooting machine learning workloads on GPU-based HPC systems
• Expertise in Cloud Computing, Virtualization and Container Technologies
• Familiarity with the HPC software stack

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $180,400 - $294,000 per year.

Microsoft will accept applications for the role until January 6, 2025.

Responsibilities

• Be part of a comprehensive systems management team focused on operational excellence and customer success
• Analyze key system metrics and telemetry to proactively identify and debug HPC system issues, build appropriate tooling, help develop processes and ensure that solutions are responsive to emerging user needs
• Partner with customers, vendors, and other teams within Azure to drive comprehensive solutions for operating world class Supercomputers in the public cloud environment
• Ensure that the Azure platform is performant, scalable and resilient
• Foster test-driven engineering culture to reduce regressions and bugs in production and will set a higher bar for infrastructure quality