Job Description
- Design, develop, and maintain automated pipelines for input data ingestion and output model deployment to SAT environments.
- Collaborate with data engineering and AI/ML teams to ensure seamless integration of data and models across environments.
- Build CI/CD workflows for ML model lifecycle management using Azure Services.
- Ensure traceability, versioning, and reproducibility of datasets and models.
- Monitor pipeline performance, implement logging and alerting, and troubleshoot issues proactively.
- Maintain compliance with data governance, security, and operational standards.
- Document pipeline architecture, workflows, and operational procedures.
- Strong hands-on experience with Azure services
- Proficiency in Terraform for infrastructure provisioning and automation.
- Experience with containerization (Docker) and orchestration (ECS, EKS).
- Solid understanding of CI/CD practices for ML workflows.
- Profic...
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