MLE/MLOps consultant

Educational Requirements

Bachelor of Engineering,BSc,BTech,BBA,MTech,MSc

Service Line

Data Analytics Unit

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

Additional Responsibilities:

• 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

Technical and Professional Requirements:

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.

Preferred Skills:

Technology->AI-AI Engineering->MLOps