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MLOps Engineer - Delphic Global
MLOps Engineer
MLOps Engineer needed to migrate data science workloads from GCP to Azure Databricks, automate pipelines, implement CI/CD, and manage model lifecycle across cloud environments.
About the role
Key Responsibilities
- Lead the migration of existing machine‑learning models from Google Cloud Platform to Azure Databricks, ensuring data integrity and minimal downtime.
- Design, build, and maintain automated CI/CD pipelines for model training, testing, and deployment using tools such as GitHub Actions, Azure DevOps, or Jenkins.
- Implement robust model lifecycle management practices, including versioning, monitoring, and rollback strategies with MLflow or similar platforms.
- Develop containerized solutions (Docker, Kubernetes) to enable reproducible, scalable execution of data‑science workloads across GCP and Azure.
- Orchestrate cross‑cloud data movement, ensuring seamless ingestion from GCP storage, processing in Azure Databricks, and output back to GCP.
- Collaborate with data scientists and infrastructure teams to define standards, best practices, and security compliance for MLOps processes.
Requirements
- 3+ years of hands‑on experience in MLOps, with proven projects migrating models between cloud platforms.
- Strong proficiency in Python and container technologies (Docker, Kubernetes).
- Deep knowledge of Google Cloud Platform services and Azure Databricks, including data pipelines and storage options.
- Experience building CI/CD pipelines for machine‑learning workflows and using model tracking tools such as MLflow.
- Solid understanding of data security, governance, and identity verification processes in cloud environments.
Skills
pythoncicddockerkubernetesmlflow