ML Engineer

ML Engineer – Unity Catalog & Feature Store (Databricks)

Location: Argentina

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 life-saving 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.

We are looking for a skilled and motivated ML Engineer with deep expertise in Unity Catalog and Feature Store within Databricks to join our dynamic team. This role will focus on building and maintaining the data infrastructure that supports robust, scalable, and production-ready machine learning workflows. You will collaborate with cross-functional teams to organize data, manage access control, and enable efficient deployment and monitoring of ML models in production environments.

Key Responsibilities:

• Set up and manage Unity Catalog in Databricks to structure and secure data access across multiple teams.
• Design and operationalize Feature Stores to support machine learning models in production.
• Build scalable and efficient ETL pipelines for feature processing and serving within ML workflows.
• Collaborate with teams utilizing Databricks, Azure Cosmos DB, and other Azure-based tools to develop integrated data solutions.
• Monitor and optimize the performance and reliability of data pipelines and feature stores.
• Deploy machine learning models using Java APIM and manage containers with AKS.
• Ensure system reliability with tools such as Splunk and Datadog.

Mandatory Skills:

• Proven experience working with Unity Catalog in Databricks for data asset management and access control.
• Hands-on experience with Databricks Feature Store or equivalent tools.
• Proficiency in building and maintaining ETL pipelines using Python and Apache Spark.
• Familiarity with Azure services, including Azure Cosmos DB and Azure Container Registry (ACR).
• Solid understanding of machine learning workflows, from feature engineering to model deployment.
• Experience deploying ML models using Java, specifically Java APIM.
• Strong problem-solving skills and the ability to work collaboratively in cross-functional teams.
• Familiarity with AKS (Azure Kubernetes Service) for containerized deployment.

What You’ll Love About Working Here:

We recognize the significance of flexible work arrangements to provide support. Be it remote work, or flexible work hours, you will get an environment to maintain healthy work-life balance.

At the heart of our mission is your career growth. Our array of career growth programs and diverse professions are crafted to support you in exploring a world of opportunities.

Equip yourself with valuable certifications in the latest technologies.

What We Offer:

• Remote/Hybrid work model and long-term contract
• Pre-paid Medicine
• Connectivity bonus
• Life insurance
• Special Occasion Vouchers
• Career growth opportunities, among others!

About Capgemini

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 unlock the value of technology and build a more sustainable, more inclusive world.