About The Opportunity

This is a pipeline requisition for future opportunities. While we are not hiring immediately, we regularly seek top talent for this role and encourage you to express interest.

Cloud AI Engneer act as critical members of the Data Intelligence team. Their tasks involve researching, building, and designing the artificial intelligence responsible for machine learning and maintaining and improving existing artificial intelligence systems.

Often, a AI & Machine Learning Engineer will also serve as a critical communicator between other Data Intelligence team members, working directly with the data scientists who develop the models for building AI systems and the people who construct and run them.

How You Will Make An Impact

Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
Develop and deploy Machine Learning and Generative AI (GenAI) models using AWS SageMaker.
Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.




Prepare and structure data for advanced AI and GenAI solutions.
Ensure seamless integration of data and AI solutions within cloud architectures, including data security and governance aspects.
Document and rigorously test models and workflows to meet accuracy and performance requirements.
Monitor and enhance the performance of Machine Learning models and services in production.
Manage Data Lake architectures, tailoring data to the needs of Machine Learning and GenAI workloads. (Desired)

What You Will Bring To The Table

Proven experience as a Machine Learning Engineer or in Data Science roles, with strong skills in data pipelines and Machine Learning model development.
Experience working in cloud environments (AWS) for at least 2 years.
Solid proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or similar.
Advanced English level.
Experience using SageMaker and other AWS data services: S3, AWS Glue, At

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