MLOps Engineer Must-Have Skills Strong proficiency in Python/PySpark, especially in analytical contexts DevOps and CI/CD expertise with Git proficiency Ability to build and maintain CI/CD pipelines Code refactoring skills and knowledge of software development principles (OOPs, SOLID) Unit testing and exception handling expertise Deep understanding of ML techniques and their applications End-to-end ML lifecycle experience Experience with model deployment and cloud services Model monitoring and drift detection capabilities Knowledge to develop production-ready code implementations Knowledge of unsupervised & unsupervised learning techniques (Regression, Classification, clustering, etc) SQL proficiency Good To Have Skills Experience in the CPG/Retail domain Cloud computing and big data technologies expertise Experience with containerization and deployment of ML models Familiarity with MLOps-specific tools Experience with data visualization and data imputation techniques Background in software development practices and agile methodologies Experience automating model testing and validation processes Soft Skills Strong communication skills to collaborate with data scientists, data engineers, and architects Problem-solving abilities and analytical thinking Attention to detail, especially for audit-ready code Ability to work in cross-functional teams Technical documentation capabilities

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Ml Engineer