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 : 6–8 years
Shift: 1 PM – 10 PM IST (Monday to Friday)
Target onboarding: Immediate
Number of positions: 01
Location: PAN India with preference at Bangalore.
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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 : 6–8 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
Skills: ml,cd,python,ci
