Job Description
About the Client
Our client is a large, technology-driven organisation undergoing significant digital and AI transformation. The team sits within a central MLOps and Data Platform function, responsible for building scalable, secure, and production-grade data foundations that enable machine learning, analytics, and generative AI use cases across the business.
Key Responsibilities
Design, build, and maintain robust data pipelines and platforms that support ML training, experimentation, and production deployment.
Work closely with data scientists, ML engineers, and MLOps teams to operationalise machine learning models at scale.
Develop and optimise batch and streaming data pipelines for large structured and unstructured datasets.
Implement data solutions that support feature engineering, model monitoring, and retraining workflows.
Ensure high standards of data quality, reliability, security, and performance across the ML lifecycle.
Contribute to the evolution of ML...
Our client is a large, technology-driven organisation undergoing significant digital and AI transformation. The team sits within a central MLOps and Data Platform function, responsible for building scalable, secure, and production-grade data foundations that enable machine learning, analytics, and generative AI use cases across the business.
Key Responsibilities
Design, build, and maintain robust data pipelines and platforms that support ML training, experimentation, and production deployment.
Work closely with data scientists, ML engineers, and MLOps teams to operationalise machine learning models at scale.
Develop and optimise batch and streaming data pipelines for large structured and unstructured datasets.
Implement data solutions that support feature engineering, model monitoring, and retraining workflows.
Ensure high standards of data quality, reliability, security, and performance across the ML lifecycle.
Contribute to the evolution of ML...
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