Mlops Engineer

**MACHINE LEARNING ENGINEER (México, Remote)**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.**YOUR ROLE**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.**- 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**YOUR PROFILE**- Good conversational **English**(C1, C2)- 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 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**WHAT YOU'LL LOVE ABOUT WORKING HERE**- At Capgemini Engineering, we encourage flexibility in how, when, and where people get their work done, allowing a better work-life balance, and greater empowerment. They partner with their managers to find an arrangement that works best for their role and their circumstances.- If you join us, you’ll find we’ll support your career at every stage. We’ll connect you with diverse, worldwide networks, and help you take your skills to the next level.- At Capgemini Engineering, Team Spirit is very strong, and People feel supported. I’m not just part of a team - I’m part of a community. A friendly, can-do group of people for whom collective effort comes naturally.**ABOUT CAPGEMINI**Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 300,000 team members in nearly 50 countries. With its strong 50-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering, and platforms.**Get the future you want