Job description

We have an immediate Openings with Our Direct Client for a Long term contract position. Job Title: Sr MLOps Engineer With Azure Exp Location: Dallas TX (onsite Role) Duration: 12+ Months Qualification • 10+ years of experience in implementing MLOps processes and solutions within the Azure ecosystem. • Proficiency in Azure cloud services, including AzureML, Azure DevOps, Azure Kubernetes Service (AKS), Azure Databricks, and other relevant Azure services. • Strong knowledge of machine learning frameworks and tools compatible with Azure and scikit-learn. • Familiarity with Azure Resource Manager templates and Infrastructure as Code (IaC). • Experience with version control systems, particularly Git, and CI/CD pipelines using Azure DevOps. • Should have implemented test automation scripts to validate the deployment process. • Scripting and coding skills, with proficiency in languages such as Python, PySpark, PowerShell, or Azure CLI. • Understanding of security and compliance standards within the Azure ecosystem. • Should have executed atleast 2 Azure MLOps project • Should have worked atleast 2 projects using Agile/SAFe methodology • Problem-solving and troubleshooting abilities. • Should have cross global location experience and been part of a team with atleast 15+ members in a global delivery model • Azure-specific certifications can be a plus, such as Microsoft Certified: Azure AI Engineer Associate or Microsoft Certified: Azure DevOps Engineer Expert. Responsibilities • Collaborate with data scientists and engineers to design, build, and maintain Azure-based MLOps pipelines for automating machine learning model deployment, monitoring, and maintenance. • Configure and manage Azure cloud resources to support machine learning workloads efficiently. • Collaborate with Azure administrators to ensure scalable and reliable infrastructure for MLOps. • Implement Azure-based deployment pipelines for deploying machine learning models into production environments. • Implement test automation script to monitor & validate the deployment process. • Work alongside data engineers to develop and maintain data pipelines on Azure, ensuring proper data governance and integration with MLOps pipelines. • Implement data versioning, data lineage tracking, and other data management best practices. • Implement test automation script to monitor & validate the deployment process. • Ensure that MLOps processes on Azure adhere to security and regulatory standards. • Monitor and troubleshoot application and infrastructure issues and implement solutions in a timely manner • Collaborate with development and BI teams to ensure code quality and application performance • Stay updated on the latest Azure MLOps tools and services and integrate improvements into existing processes.

Requirements