Machine Learning Engineer
Tasks
- Build and maintain data pipelines for preprocessing and transformation
- Document processes and best practices
- Ensure data security and compliance
- Implement CI/CD pipelines
- Integrate and deploy machine learning models
- Manage cloud resources and optimize performance
- Monitor model performance and system health
- Set up tools for deploying and monitoring models
- Update and improve MLOps and AIOps pipelines
Perks/Benefits
- Coaching and training
- Educational platforms access
- Flexible schedule
- Hybrid work model
- Income protection
- Private health and life insurance
- Support for certifications
- Travel opportunities
- Volunteerism opportunities
Skills/Tech-stack
AIOps | AWS SageMaker | Amazon Web Services | Automated testing | Azure Synapse | Azure Synapse Analytics | CI/CD | Cloud Resource Management | Cloud platform | Cloudera | Containerization | Data Preprocessing | Data Transformation | Data pipeline | Docker | Google Cloud | Google Cloud Platform | Infrastructure as Code | Kubeflow | Kubernetes | MLOps | MLflow | Machine Learning | Microsoft Azure | Model Monitoring | Resource Management | Synapse Analytics | System Administration | Web Services | “as-code”
Education
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