Site Reliability Engineer
Site Reliability Engineer
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Job Description
Job Summary
We are seeking an experienced Site Reliability Engineer with AI MLOps to support the development and optimization of our ERP product primarily in Azure and Windows environments. This role combines MLOps expertise with Site Reliability Engineering (SRE) principles to ensure the reliable scalable and costefficient deployment of AI models. The ideal candidate will focus on improving security compliance and operational efficiency collaborating with North American and global teams to meet business objectives.
Key Responsibilities
AI MLOps Pipeline: Build and optimize CI/CD pipelines to automate the training testing and deployment of AI models on Azure with a strong emphasis on improving efficiency and reducing costs.
Azure Infrastructure Management: Manage and maintain scalable secure infrastructure using Azure services like Azure Machine Learning AKS and Virtual Machines. Continuously optimize resource usage and implement costsaving measures.
Windows Server Management: Oversee Windowsbased servers hosted on Azure ensuring they meet performance security and compliance requirements while also identifying and executing costsaving opportunities.
Cost Optimization: Analyze and manage infrastructure costs by identifying unused or underused resources and implementing optimization strategies to drive cost savings.
Monitoring & Performance Optimization: Monitor the health performance and costs of AI models and services using Azure Monitor NewRelic and other tools. Identify performance bottlenecks and optimize for both operational efficiency and cost reduction.
Model Versioning & Governance: Assist in managing model version control governance and lifecycle processes with a focus on costeffective operations.
Crossfunctional Collaboration: Collaborate with data scientists AI engineers and software developers to support the efficient deployment and operationalization of AI models while actively seeking ways to minimize costs.
Incident Management & Automation: Participate in incident resolution and automate tasks to reduce manual work improve system reliability and lower operational overhead.
Security & Compliance Assurance: Ensure AI/ML workloads comply with security and regulatory standards implementing costefficient solutions to enhance security and data protection.
Qualifications
Experience: 2 5 years in MLOps SRE or similar roles focusing on Azure and Windows environments.
Cloud Skills: Proficient in Azure services managing infrastructure and Windows workloads.
SRE Knowledge: Familiar with Site Reliability Engineering principles like monitoring and automation.
DevOps: Handson experience with CI/CD tools like Azure DevOps.
Scripting: Skilled in PowerShell and Python for automation.
Containers: Knowledge of Docker and Kubernetes for deploying AI/ML applications.
Windows Admin: Strong experience managing Windows Servers and related services.
AI/ML Knowledge: Understanding of AI/ML workflows and model deployment.
NicetoHave
Experience with InfrastructureasCode tools like Terraform.
Azure certifications (e.g. Azure AI Engineer Azure DevOps Engineer)
Experience implementing costsaving strategies in cloud environments
Soft Skills
Strong problemsolving skills with the ability to troubleshoot complex issues.
Excellent communication skills and the ability to collaborate effectively with crossfunctional teams.
A passion for innovation and continuous improvement in AI/ML systems.
Employment Type
Full-Time
