Azure MLOps Engineer

• Role & responsibilities:

Looking for 5 to 8 years experience of ML Engineer with strong Azure Cloud DevOps with even stronger DABs DevOps skills with even stronger DABs Databricks Asset Bundles implementation knowledge.

1 Azure Cloud Engineer
2 Azure DevOps CICD experienced in DABs3 ML Engineer for deployment Translate business requirement into technical solution Implementation of MLOPS Scalable solution using AIML and reduce the risk of Fraud and other fiscal crisis Creating MLOPS Architecture and implementing it for multiple models in a scalable and automated way Designing and implementing end to end ML solutions Operationalize and monitor machine learning models using high end tools and technologies Design implementation of DevOps principles in Machine Learning Data Science quality assurance and testing Collaborate with data scientists engineers and other key stakeholders

Preferred candidate profile:

• Azure Cloud Engineering
  Design implement and manage scalable cloud infrastructure on Microsoft AzureEnsure high availability performance and security of cloud based applicationsCollaborate with cross functional teams to define and implement cloud solutionsAzure DevOps CICDDevelop and maintain CICD pipelines using Azure DevOpsAutomate deployment processes to ensure efficient and reliable software deliveryMonitor and troubleshoot CICD pipelines to ensure smooth operationDABs Databricks Asset Bundles ImplementationLead the implementation and management of Databricks Asset BundlesOptimize data workflows and ensure seamless integration with existing systemsProvide expertise in DABs to enhance data processing and analytics capabilitiesMachine Learning DeploymentDeploy machine learning models into production environmentsMonitor and maintain ML models to ensure optimal performanceCollaborate with data scientists and engineers to integrate ML solutions into applications.