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MACHINE LEARNING ENGINEER - SENIOR

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Descripcion del empleo

Why Capgemini Engineering?



Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unluck the value of technology and build a more sustainable, more inclusive world.



Machine Learning Engineer

We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows. You will work on organizing data, managing access, and enabling machine learning models to operate efficiently in production



Key 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

• 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



Mandatory Skills

• Strong experience with Unity Catalog in Databricks for managing data assets and access control

• Strong experience with Unity Catalog in Databricks for managing data assets and access control

• Hands-on experience working with Databricks Feature Storeor 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 using Java(specifically Java APIM) to deploy Machine Learning Models

• 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



About Capgemini

At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to lifesaving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same.

24 de abril · Salario: A convenir