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Microsoft AI is looking for experienced Member of Technical Staff, High Performance Computing Engineers to help build and scale the infrastructure that trains our frontier models and powers the next evolution of our personal AI, Copilot. This role offers the unique opportunity to work on some of the largest scale supercomputers in the world.
Job Responsibility:
Design, operate, and maintain large-scale HPC environments
Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes)
Serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar)
Develop and maintain automation and tooling using Bash and/or Python
Partner closely with researchers and engineers to support their workloads, troubleshoot cluster usage issues, and triage failed or underperforming jobs
Drive work forward independently by navigating ambiguity and technical roadblocks
Enjoy working in a fast-paced, design-driven product development environment
Embody our Culture and Values
Requirements:
Bachelor’s degree in computer science, or related technical field AND 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters
4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.)
4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP
OR equivalent experience
Nice to have:
Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters
6+ years experience working with high-scale training clusters
6+ years experience building scalable services on top of public cloud infrastructure
OR equivalent experience
Experience with LLM training clusters
Experience working with AI platforms, frameworks, and APIs
Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models
Experience working with large-scale HPC or GPU systems (ex. NVIDIA H100/GB200 or equivalent)
Ability to identify, analyze, and resolve complex technical issues
Dedication to writing clean, maintainable, and well-documented code
Demonstrated interpersonal skills and ability to work closely with cross-functional teams
Ability to clearly communicate complex technical concepts
Passion for learning new technologies
Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements
Proven ability to collaborate and contribute to a positive, inclusive work environment