Description

You will design, implement, and operationalize end-to-end machine learning solutions within an Azure environment.

Responsibilities

• Design and implement scalable MLOps architectures to automate model deployment and monitoring.
• Develop and maintain ETL pipelines using Azure Data Factory and Databricks.
• Translate business requirements into technical solutions and implement MLOps to reduce fiscal risk.
• Apply DevOps principles to machine learning workflows, ensuring quality assurance and testing.
• Collaborate with data scientists and engineers to deliver automated, scalable ML solutions.

Required Skills

• 5+ years of experience in machine learning or related engineering roles.
• Strong proficiency in Python.
• Extensive experience with Azure Cloud and Azure DevOps CI/CD for model deployment.
• Hands-on experience with Databricks Asset Bundles (DABs) and custom implementations.
• Expertise in developing ETL pipelines using Azure Data Factory and Databricks.
• Deep knowledge of Azure DevOps and Git-based workflows.
• Ability to implement scalable MLOps solutions.
• Any Graduate degree.

Preferred Skills

• Experience with Databricks Lakehouse, Delta Live Tables, and Unity Catalog.
• Ability to build and optimize Lakehouse using Delta Lake and Databricks SQL.
• Proficiency in writing efficient PySpark code for data transformation and aggregation.

Key Skills

Education

Any Graduate