Jobs via Dice
Member of Technical Staff - Site Reliability Engineer
Jobs via Dice, Redmond, Washington, United States, 98052
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 are 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. 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/Google Cloud Platform 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. Compensation
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: ;br> Application Note
Microsoft will accept applications and processes offers for these roles on an ongoing basis. #MicrosoftAI #Copilot CLICK TO APPLY Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries Software Development
#J-18808-Ljbffr
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 are 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. 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/Google Cloud Platform 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. Compensation
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: ;br> Application Note
Microsoft will accept applications and processes offers for these roles on an ongoing basis. #MicrosoftAI #Copilot CLICK TO APPLY Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries Software Development
#J-18808-Ljbffr