Software Engineer II: HPC & AI Benchmarking

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Azure is building accelerated supercomputers at unprecedented scales to facilitate the massive computational demands of the world’s leading High-Performance Computing (HPC) and Artificial Intelligence (AI) workflows. The Specialized Workflows team is responsible for creating representative HPC & AI workflows for these systems, measuring and optimizing their performance, and ensuring they meet the high expectations of Azure’s customers. The team also publishes blog posts and research papers in leading conferences and submits results to MLPerf and the Top 500 list of the world’s fastest supercomputers.

As a Software Engineer in this team, you will be responsible for creating and running benchmarks and representative workflows, and analyzing the performance of Azure’s supercomputers. You will also work on creating automation to run these workflows as part of system validation for our largest supercomputers.

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.

Required/Minimum Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• 1+ year experience with AI and/or HPC workflows and/or benchmarks
• 1+ year experience with test and/or benchmark automation

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.

Additional or Preferred Qualifications:

• Master's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• 1+ year(s) experience with performance analysis and tuning of large-scale supercomputers
• Knowledge of how large language models are implemented (key computational kernels, parallelization techniques, etc.)
  
• Knowledge of common HPC applications

Software Engineering IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

Microsoft will accept applications for the role until July 23, 2025.

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• Works with appropriate stakeholders to determine requirements for High-Performance Computing (HPC) and Artificial Intelligence (AI) benchmarks, workflows, and cluster validation tests.
• Contributes to the identification of dependencies, and the development of design documents for benchmarks, workflows, and validation tests with little oversight.
• Creates and implements benchmark, workflow, and validation code, reusing code as applicable.
• Collaborates with partner teams to identify and resolve issues with Azure supercomputers that are found during benchmarking and validation.
• Remains current in skills by investing time and effort into staying abreast of current developments that will improve the availability, reliability, efficiency, observability, and performance of products while also driving consistency in monitoring and operations at scale.