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MLE/MLOps

MLE/MLOps

Infosys

3 - 7 years

0 Lacs

karnataka

Posted:3 days ago| Platform: Shine logo

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Skills Required

data analysis debugging mlops solutions client consulting ml pipelines operationalization of ml models cloud technologies

Work Mode

On-site

Job Type

Full Time

Job Description

As a candidate for the position, you will be expected to have the following Educational Requirements: - 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. Your key responsibilities in this role will include: - Understanding the requirements from the business and translating them into appropriate technical requirements. - Being responsible for the successful delivery of MLOps solutions and services in client consulting environments. - Defining key business problems to be solved, formulating high-level solution approaches, identifying data to solve those problems, developing, analyzing/drawing conclusions, and presenting them to the client. - Assisting clients with operationalization metrics to track the performance of ML Models. - Helping the team with ML Pipelines from creation to execution. - Guiding the team to debug issues with pipeline failures. - Understanding and taking requirements on Operationalization of ML Models from Data Scientist. - Engaging with Business/Stakeholders with status updates on progress of development and issue fix. - Setting up standards related to Coding, Pipelines, and Documentation. - Researching new topics, services, and enhancements in Cloud Technologies. If any additional details about the company were provided in the job description, it should be included here.,

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MLE/MLOps