Member of Technical Staff - Site Reliability Engineer
Microsoft
Software Engineering, IT
USD 117,200-229,200 / year + Equity
Posted on Oct 2, 2025
Member of Technical Staff - Site Reliability Engineer
Redmond, Washington, United States
Date posted
Oct 01, 2025
Job number
MIC085943
Work site
Microsoft on-site only
Role type
Individual contributor
Profession
Software Engineering
Discipline
Site Reliability Engineering
Employment type
Full-time
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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 Site Reliability Engineer (SRE) to join our 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 work closely with ML researchers, data engineers, and product developers to design and operate the platforms that power training, fine-tuning, and serving generative AI 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 AI model training and inference systems.
- Observability: Design and maintain monitoring, alerting, and logging systems to provide real-time visibility into model serving pipelines and infra.
- Performance Optimization: Analyze system performance and scalability, optimize resource utilization (compute, GPU clusters, storage, networking).
- Automation & Tooling: Build automation for deployments, incident response, scaling, and failover in hybrid cloud/on-prem 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
- 4 years of experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering roles.
Other 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).
Preferred Qualifications
- 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.
- Work on cutting-edge infrastructure that powers the future of Generative AI.
- Collaborate with world-class researchers and engineers.
- Impact millions of users through reliable and responsible AI deployments.
- Competitive compensation, equity options, and comprehensive benefits.
Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $117,200 - $229,200 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 $153,600 - $250,200 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
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
#MicrosoftAI #Copilot
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect
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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.