Azure MLOps Engineer

Job Description

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 DABs 3 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 Azure Ensure high availability performance and security of cloud based applications Collaborate with cross functional teams to define and implement cloud solutions Azure DevOps CICD Develop and maintain CICD pipelines using Azure DevOps Automate deployment processes to ensure efficient and reliable software delivery Monitor and troubleshoot CICD pipelines to ensure smooth operation DABs Databricks Asset Bundles Implementation Lead the implementation and management of Databricks Asset Bundles Optimize data workflows and ensure seamless integration with existing systems Provide expertise in DABs to enhance data processing and analytics capabilities Machine Learning Deployment Deploy machine learning models into production environments Monitor and maintain ML models to ensure optimal performance Collaborate with data scientists and engineers to integrate ML solutions into applications.