Overview
On Site
USD 117,200.00 - 229,200.00 per year
Full Time
Skills
AIM
Systems Engineering
Accountability
Microsoft Office
Law
Real-time
Performance Tuning
Scalability
SAN
Build Automation
Failover
CPU
Incident Management
Privacy
Regulatory Compliance
Research
Workflow
Reliability Engineering
DevOps
Docker
Orchestration
Continuous Integration
Continuous Delivery
Cloud Computing
Microsoft Azure
Amazon Web Services
Google Cloud Platform
Google Cloud
Grafana
Scripting
Python
Bash
Computer Networking
Storage
Machine Learning (ML)
Training
High Performance Computing
HPC
Kubernetes
Capacity Management
Optimization
GPU
Generative Artificial Intelligence (AI)
Collaboration
Artificial Intelligence
Software Engineering
IC
Integrated Circuit
Internal Communications
Microsoft
SAP BASIS
Job Details
CLICK TO APPLY 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
Required Qualifications
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: ;br>
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
#MicrosoftAI #Copilot
CLICK TO APPLY
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.
Required Qualifications
- 4 years of experience in Site Reliability Engineering, DevOps, or Infrastructure Engineering roles.
- 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).
- 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.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: ;br>
Microsoft will accept applications and processes offers for these roles on an ongoing basis.
#MicrosoftAI #Copilot
CLICK TO APPLY
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.