ML Engineers

What You Will Do -

• Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
• Design and operationalize Feature Stores to support machine learning models in production
• Build efficient data pipelines to process and serve features to ML workflows
• Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
• Monitor and optimize the performance of pipelines and feature stores

What We are Looking For -

• Strong experience with Unity Catalog in Databricks for managing data assets and access control
• Hands-on experience working with Databricks Feature Store or similar solutions
• Knowledge of building and maintaining scalable ETL pipelines in Databricks
• Familiarity with Azure tools like Azure Cosmos DB and ACR
• Understanding of machine learning workflows and how feature stores fit into the pipeline
• Strong problem-solving skills and a collaborative mindset
• Proficiency in Python and Spark for data engineering tasks
• Experience with monitoring tools like Splunk or Datadog to ensure system reliability
• Familiarity with AKS for deploying and managing containers