Machine Learning Engineer / MLOps Consultant

MLE/MLOps consultant

Educational Requirements (any of the following): • Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record. • Bachelor's degree in a quantitative discipline (e.g., Operation Research, Statistics, Mathematics) or significant relevant coursework with consistent academic track record. Additional Academic Qualification (good to have): • Masters in any area related to Science, Operation Research, Mathematics and Statistics with consistent academic track record. • PhD in any stream. • Good knowledge on software configuration management systems • Strong business acumen, strategy and cross-industry thought leadership • Awareness of latest technologies and Industry trends • Logical thinking and problem solving skills along with an ability to collaborate • Two or three industry domain knowledge • Understanding of the financial processes for various types of projects and the various pricing models available • Client Interfacing skills • Knowledge of SDLC and agile methodologies • Project and Team management • 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