Machine Learning Ops and Data Engineer
Tasks
- Deploy machine learning models into production environments
- Design maintain troubleshoot and optimize ETL data pipelines
- Develop automation for model deployment updates scaling and data processing
- Ensure reliable operation of analytical data warehouse
- Ensure timely high quality data availability for stakeholders
- Implement monitoring for data pipelines and machine learning models
- Investigate and resolve performance issues across data warehouse ETL and deployments
- Maintain technical documentation for data processes model deployments and configurations
- Support cloud based analytical reporting and machine learning infrastructure
- Troubleshoot debug upgrade and improve pipelines and deployment processes
Perks/Benefits
- Collaborative team culture
- Continuous improvement culture
- Learning opportunities
- Modern technical environment
Skills/Tech-stack
Azure | CI/CD | Containerization | Data Warehouse | Docker | Docker Compose | ETL | MLOps | Machine Learning | Machine Learning Model | Machine learning model deployment | Model Deployment | Monitoring | Python | SQL | Scikit-learn | Version control | XGBoost
Education
N/A
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