ML / Data Engineer – Data Science Enablement
Tasks
- Build and maintain scalable data and ML pipelines
- Create model evaluation validation and monitoring frameworks
- Develop ML ready datasets and feature pipelines
- Develop deployment workflows and APIs
- Enable end to end ML lifecycle management
- Ensure data governance security and architecture compliance
- Follow engineering best practices for code quality testing and CI CD
- Implement batch and real time scoring pipelines
- Monitor track and operationalize model outputs
- Productionize machine learning models
- Support model tracking and experiment management
- Translate analytical solutions into production systems
Perks/Benefits
- N/A
Skills/Tech-stack
API | AWS | Apache Spark | Azure | CI/CD | Cloud platform | Containerization | Data Drift | Data Drift Detection | Databricks | Drift Detection | Feature Engineering | Git | Google Cloud | Google Cloud Platform | MLflow | Machine Learning | Model Monitoring | Orchestration | PySpark | Python | SQL
Education
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