Description

You will design and manage machine learning data infrastructure and deployment workflows.

Responsibilities

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

Required Skills

• 5+ years of experience as a Machine Learning Engineer or in a similar role.
• Strong experience with Unity Catalog in Databricks for data asset and access control management.
• Hands-on experience with Databricks Feature Store or similar solutions.
• Proficiency in Python and Spark for data engineering tasks.
• Proficiency in Java, specifically Java APIM, to deploy machine learning models.
• Experience building and maintaining scalable ETL pipelines in Databricks.
• Familiarity with Azure tools including Azure Cosmos DB and ACR.
• Experience with monitoring tools such as Splunk or Datadog.
• Familiarity with AKS for container deployment and management.
• Advanced English proficiency.

Preferred Skills

• Understanding of machine learning workflows and feature store integration.

Key Skills

Education

Any Gradute