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Jobs or company...
A

ML (Machine Learning) Engineers

  • Full Time, onsite
  • Aeron Smith
  • Hybrid3 days in office, United States of America
Salary undisclosed
Checking job availability...
Original
Simplified

ML (Machine Learning) Engineers: with Unity Catalog / Databricks / Feature Store/ Java 11/ Python/ Kubernetes/

The ML Engineers will be supporting 3 web services applications tech stack - Java 11/ Python/ Azure/ AKS/ APIM

Seattle based Client
Hybrid / 3 days office in Seattle WA
Visa: USC/ GC

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 with Java
  • 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.

Required Key skills:

Databricks Unity Catalog: Data governance, access control, data asset management.
Databricks Feature Store: Feature engineering, feature serving, ML workflow integration.
ETL Pipeline Development (Databricks): Data processing, data pipeline construction, data integration.
Azure Tools: Azure Cosmos DB, Azure Container Registry (ACR).
Machine Learning Workflows: Model training, deployment, and monitoring; understanding of feature store's role.
Programming Languages: Java, Python, Spark (for data engineering).
Monitoring Tools: Splunk, Datadog (system reliability and performance monitoring).
Containerization: Azure Kubernetes Service (AKS) for deployment and ent.
Problem-Solving & Collaboration: Ability to work effectively in a team and address technical challenges

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job

ML (Machine Learning) Engineers: with Unity Catalog / Databricks / Feature Store/ Java 11/ Python/ Kubernetes/

The ML Engineers will be supporting 3 web services applications tech stack - Java 11/ Python/ Azure/ AKS/ APIM

Seattle based Client
Hybrid / 3 days office in Seattle WA
Visa: USC/ GC

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 with Java
  • 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.

Required Key skills:

Databricks Unity Catalog: Data governance, access control, data asset management.
Databricks Feature Store: Feature engineering, feature serving, ML workflow integration.
ETL Pipeline Development (Databricks): Data processing, data pipeline construction, data integration.
Azure Tools: Azure Cosmos DB, Azure Container Registry (ACR).
Machine Learning Workflows: Model training, deployment, and monitoring; understanding of feature store's role.
Programming Languages: Java, Python, Spark (for data engineering).
Monitoring Tools: Splunk, Datadog (system reliability and performance monitoring).
Containerization: Azure Kubernetes Service (AKS) for deployment and ent.
Problem-Solving & Collaboration: Ability to work effectively in a team and address technical challenges

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
Report this job