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ML Engineer

Techgene

 

Seattle, WA, USA

Posted On: 3 days ago
Experience: 5+ years
Availability: Hybrid
Openings: 1
Category: ML Engineers
Tenure: No Preference/Any
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Description

You will build and manage the data infrastructure supporting production machine learning models.

This role is on-site.

Responsibilities

  • 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.
  • Monitor and optimize the performance of pipelines and feature stores.
  • Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions.

Required Skills

  • 5+ years of experience in machine learning or data engineering roles.
  • Strong experience with Unity Catalog in Databricks for managing data assets and access control.
  • Hands-on experience with Databricks Feature Store or similar solutions.
  • Proficiency in Python and Spark for data engineering tasks.
  • Knowledge of building and maintaining scalable ETL pipelines in Databricks.
  • Familiarity with Azure tools including Azure Cosmos DB and ACR.
  • Experience with monitoring tools like Splunk or Datadog.
  • Familiarity with AKS for deploying and managing containers.

Education

Any Graduate

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