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Candidates with strong Python + Databricks + CI/CD + Production MLOps support experience who have worked on monitoring, troubleshooting, deployment, and model/data drift management in production ML environments Experience Range : 68 years Shift: 1 PM 10 PM IST (Monday to Friday) Target onboarding: Immediate Number of positions: 01 Location: PAN India with preference at Bangalore. >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Key Responsibilities: - Monitor end-to-end pipeline execution and ensure smooth daily runs - Identify, debug, fix issues, and rerun pipelines during failures - Collaborate cross-functionally to resolve dependencies and blockers - Implement preventive health checks and robust logging for proactive issue detection - Design and maintain dashboards for data validation and quality checks - Perform data validation and ensure integrity across pipeline outputs - Analyze model performance using statistical metrics and monitor data/feature/concept drift - Build automated alerts/notifications for pipeline failures - Develop agent-based solutions for automated monitoring and debugging - Enhance and maintain CI/CD pipelines, including implementing data-based authentication and building new CI/CD workflows - Ensure proactiveness & timely deliverables with strong communication, ownership, and stakeholder updates - Apply model explainability techniques and leverage GenAI for insights and summarization Technical Requirements Python - Strong Python skills & solid understanding of OOP (including inheritance) - Hands-on experience with unit testing, regression testing, and testing frameworks such as pytest - Experience with pandas and PySpark etc. - Knowledge of software design patterns Databricks - Understanding of Databricks architecture and components - Experience with Databricks Asset Bundles - Ability to build, enhance, and debug Databricks Jobs/Workflows CI/CD & Git - Knowledge of Git flows, branching strategies, and version control best practices - Experience with GitHub Actions - Ability to deploy Databricks (dbx) jobs through CI/CD pipelines - Familiarity with Azure services, including Key Vault Data/Model Monitoring - Understanding of data drift, model drift, and concept drift - Ability to use drift indicators for identifying early-stage data quality issues - Experience with monitoring and alerting tools is a plus MLOps Engineer Production Support (Databricks & Python) Candidates with strong Python + Databricks + CI/CD + Production MLOps support experience who have worked on monitoring, troubleshooting, deployment, and model/data drift management in production ML environments Experience Range : 68 years Shift: 1 PM 10 PM IST (Monday to Friday) Target onboarding: Immediate Number of positions: 01 Location: PAN India with preference at Bangalore. >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> Key Responsibilities: - Monitor end-to-end pipeline execution and ensure smooth daily runs - Identify, debug, fix issues, and rerun pipelines during failures - Collaborate cross-functionally to resolve dependencies and blockers - Implement preventive health checks and robust logging for proactive issue detection - Design and maintain dashboards for data validation and quality checks - Perform data validation and ensure integrity across pipeline outputs - Analyze model performance using statistical metrics and monitor data/feature/concept drift - Build automated alerts/notifications for pipeline failures - Develop agent-based solutions for automated monitoring and debugging - Enhance and maintain CI/CD pipelines, including implementing data-based authentication and building new CI/CD workflows - Ensure proactiveness & timely deliverables with robust communication, ownership, and stakeholder updates - Apply model explainability techniques and leverage GenAI for insights and summarization Technical Requirements Python - Strong Python skills & solid understanding of OOP (including inheritance) - Hands-on experience with unit testing, regression testing, and testing frameworks such as pytest - Experience with pandas and PySpark etc. - Knowledge of software design patterns Databricks - Understanding of Databricks architecture and components - Experience with Databricks Asset Bundles - Ability to build, enhance, and debug Databricks Jobs/Workflows CI/CD & Git - Knowledge of Git flows, branching strategies, and version control best practices - Experience with GitHub Actions - Ability to deploy Databricks (dbx) jobs through CI/CD pipelines - Familiarity with Azure services, including Key Vault Data/Model Monitoring - Understanding of data drift, model drift, and concept drift - Ability to use drift indicators for Ca
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