Member of Technical Staff, Site Reliability Engineer (HPC) - MAI SuperIntelligence Team

Overview

As Microsoft continues to push the boundaries of AI, we are on the lookout for passionate individuals to work with us on the most interesting and challenging AI questions of our time. Our vision is bold and broad — to build systems that have true artificial intelligence across agents, applications, services, and infrastructure. It’s also inclusive: we aim to make AI accessible to all — consumers, businesses, developers — so that everyone can realize its benefits.

We’re looking for an experienced HPC Site Reliability Engineer (SRE) to join our High Performance Computing (HPC) infrastructure team. In this role, you’ll blend software engineering and systems engineering to keep our large-scale distributed AI infrastructure reliable and efficient. You’ll ensure that AI systems stay efficient and reliable with very high uptimes.

 

Microsoft Superintelligence Team Microsoft Superintelligence team’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.   This role is part of Microsoft AI's Superintelligence Team. The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values. Our mission is to create AI that amplifies human potential while ensuring humanity remains firmly in control. We aim to deliver breakthroughs that benefit society—advancing science, education, and global well-being.   We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models! 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.  

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

 

Responsibilities

• Reliability & Availability: Ensure uptime, resiliency, and fault tolerance of HPC clusters powering MAI model training and inference.
• Observability: Design and maintain monitoring, alerting, and logging systems to provide real-time visibility into all aspects of HPC systems including GPU, clusters, storage and networking.
• Automation & Tooling: Build automation for deployments, incident response, scaling, and failover in CPU+GPU environments.
• Incident Management: Lead on-call rotations, troubleshoot production issues, conduct blameless postmortems, and drive continuous improvements.
• Security & Compliance: Ensure data privacy, compliance, and secure operations across model training and serving environments.
• Collaboration: Partner with ML engineers and platform teams to improve developer experience and accelerate research-to-production workflows.

Qualifications

Required Qualifications

• Master's Degree in Computer Science, Information Technology, or related field AND 2+ years technical experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering
  • OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 4+ years technical experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering
  • OR equivalent experience

Preferred Qualifications

• Strong proficiency in Kubernetes, Docker, and container orchestration.
• Knowledge of CI/CD pipelines for Inference and ML model deployment.
• Hands-on experience with public cloud platforms like Azure/AWS/GCP and infrastructure-as-code.
• Expertise in monitoring & observability tools (Grafana, Datadog, OpenTelemetry, etc.).
• Strong programming/scripting skills in Python, Go