MLE Professional

Design and implement effective feature engineering using Azure tools. Set up and manage a feature store on Azure for centralized feature storage. Develop machine learning models using Azure ML, incorporating engineered features. Deploy models on Azure, ensuring seamless integration with applications. Establish monitoring systems for model performance and conduct regular maintenance. Integrate ML solutions with Azure services like Databricks and SQL Database. Remote is also fine Good in python SQL, API written and packaged deploy, some knowledge of ML, good to have knowledge on CI CD pipeline Min 5+ years Required Skills: Azure ML and Data Services: Proficient in Azure ML and relevant data services. Feature Store Management: Experience setting up and managing feature stores on Azure. Feature Engineering Techniques: Strong understanding and application of feature engineering. Programming (Python): Proficient in Python and ML frameworks . Model Deployment: Ability to deploy models as APIs on Azure. Monitoring and Optimization: Skill in implementing monitoring solutions and optimizing models. Collaboration and Communication: Effective collaboration with cross-functional teams.