Principal AI Engineer
2 weeks ago
Key Responsibilities:
Develop and implement robust machine learning pipelines using Azure Machine Learning services for a 6-month assignment. Collaborate with data scientists to transition models from development to production.
- Pipeline Development:
- Design, build and implement ML pipelines using Azure MLOps services.
- Collaborate with cross-functional teams to integrate models into production environments.
- Strong knowledge of Azure Databricks is required.
- Automation and Deployment:
- Automate the training, deployment and monitoring of ML models using Azure DevOps.
- Implement CI/CD best practices for model updates and versioning.
- Monitoring and Maintenance:
- Monitor deployed models to ensure operational standards are met.
- Troubleshoot and resolve production issues related to ML models.
- Documentation and Compliance:
- Maintain accurate documentation of ML processes and pipelines.
- Ensure compliance with data governance and security standards.
- Collaboration:
- Work effectively with data engineers, software developers and business stakeholders.
- Provide technical guidance on ML best practices.
Technical Skills:
- Required: Azure MLOps, Azure Databricks, Python, PyTorch
- Additional: TensorFlow, Scikit-learn, Docker, Kubernetes, Azure DevOps, MLflow, Kubeflow, Azure Monitor, Application Insights
- Programming Languages: Python or R
- Databases: Azure Data Lake, Azure SQL Database
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