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 AIs 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
Masters Degree in Computer Science, Information Technology, or related field AND 2+ years technical experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering
OR
Bachelors 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, or Bash.
Solid knowledge of distributed systems, networking, and storage.
Experience running large-scale GPU clusters for ML/AI workloads (preferred).
Familiarity with ML training/inference pipelines.
Experience with high-performance computing (HPC) and workload schedulers (Kubernetes operators).
Background in capacity planning & cost optimization for GPU-heavy environments.
Software Engineering IC5
The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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
Software Engineering IC4
The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations, and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.