MLE/MLOps, OOPs Python, Data Bricks,Azure

Responsibilities

• Understand the requirements from the business and translate it into an appropriate technical requirement. • Responsible for successful delivery of MLOps solutions and services in client consulting environments; • Define key business problems to be solved; formulate high level solution approaches and identify data to solve those problems, develop, analyze/draw conclusions and present to client. • Assist clients with operationalization metrics to track performance of ML Models • Help team with ML Pipelines from creation to execution • Guide team to debug on issues with pipeline failures • Understand and take requirements on Operationalization of ML Models from Data Scientist • Engage with Business / Stakeholders with status update on progress of development and issue fix • Setup Standards related to Coding, Pipelines and Documentation • Research on new topics, services and enhancements in Cloud Technologies