Azure ML Engineer
Tasks
- Build and maintain MLOps processes with CI CD and automated testing
- Collaborate with data engineers architects stakeholders and vendors
- Create reusable ML platform components and documentation
- Define Azure resources and deployment patterns with cost optimization
- Deploy and operate machine learning models
- Design and implement machine learning pipelines on Azure and Databricks
- Implement infrastructure as code for ML workflows
- Integrate ML solutions with lakehouse data platforms
- Monitor retrain and manage model versions
- Review vendor solutions for security and operational standards
Perks/Benefits
- Home office
- Private health insurance
- Professional development support
- SZÉP Card
- Team building events
- Training opportunities
Skills/Tech-stack
Access Control | Apache Spark | Automated testing | Azure Databricks | Azure DevOps | Azure Machine Learning | Azure Resource | Azure Resource Management | Bicep | CI/CD | Cost Optimization | Data Governance | Data Lineage | Data Modelling | Data Quality | Data Transformation | Databricks Compute | Delta Lake | Deployment Patterns | Git | Identity Management | Infrastructure as Code | Lakehouse Architecture | MLflow | Machine Learning | Metadata Management | Monitoring | Networking | PySpark | Python | Resource Management | Security | Terraform | “as-code”
Education
N/A
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