•    Design, develop, and maintain end to end data pipelines for ML and AI applications, including data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment.
•    Responsible for designing and implementing robust data pipelines and deploying machine learning models using Docker based solutions.
•    Collaborate with data scientists and Operations Intelligence Architect to define requirements, design data pipelines, and integrate ML models into production systems.
•    Develop and implement data quality and monitoring mechanisms to ensure the reliability and accuracy of data pipelines and ML models.
•    Stay up to date with the latest advancements in ML Ops and data engineering technologies, and evaluate emerging tools and frameworks for potential adoption.
•    Solid understanding of software engineering best practices, version control systems e.g., Git, and continuous integration and deployment CI/CD pipelines.
•    Integrate machine learning pipelines and model deployment workflows into existing CI/CD pipelines and infrastructure.
•    Must be a polyglot with proficiency in programming languages such as Python and capability to learn and adapt to new programming languages that project demands