Sr. MLOps Engineer with AZURE and LLM exp - Dallas, TX (Onsite)

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.

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.