Responsibilities
Technical knowledge- has expertise in cloud technologies, specifically MS Azure, and services with hands on coding to – • Expertise in Object Oriented Python Programming with 4 -5 years’ experience. • DevOps Working knowledge with implementation experience - 1 or 2 projects a minimum • Hands-On MS Azure Cloud knowledge • Understand and take requirements on Operationalization of ML Models from Data Scientist • Help team with ML Pipelines from creation to execution • List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup • Assist team to coding standards (flake8 etc) • Guide team to debug on issues with pipeline failures • Engage with Business / Stakeholders with status update on progress of development and issue fix • Automation, Technology and Process Improvement for the deployed projects • Setup Standards related to Coding, Pipelines and Documentation • Adhere to KPI / SLA for Pipeline Run, Execution • Research on new topics, services and enhancements in Cloud Technologies
Technical Requirements
Education and Experience: • Overall, 6 to 8 years of experience in Data driven software engineering with 3-5 years of experience designing, building and deploying enterprise AI or ML applications with at least 2 years of experience implementing full lifecycle ML automation using MLOps(scalable development to deployment of complex data science workflows) • Bachelors or Master’s degree in Computer Science Engineering or equivalent • Domain experience in Retail, CPG and Logistics etc. • Azure Certified – DP100, AZ/AI900
Preferred Skills
Technology->Data Science->Machine Learning
Additional Responsibilities
Domain / Technical / Tools Knowledge: • Object oriented programming, coding standards, architecture & design patterns, Config management, Package Management, Logging, documentation • Experience in Test Driven Development and experience in using Pytest frameworks, git version control, Rest APIs • Azure ML best practices in environment management, run time configurations (Azure ML & Databricks clusters), alerts. • Experience designing and implementing ML Systems & pipelines, MLOps practices and tools such a MLFlow, Kubernetes, etc. • Exposure to event driven orchestration, Online Model deployment • Contribute towards establishing best practices in MLOps Systems development • Proficiency with data analysis tools (e.g., SQL, R & Python) • High level understanding of database concepts/reporting & Data Science concepts • Hands on experience in working with client IT/Business teams in gathering business requirement and converting into requirement for development team • Experience in managing client relationship and developing business cases for opportunities • Azure AZ-900 Certification with Azure Architecture understanding is a plus
Educational Requirements
MCA,MSc,Bachelor of Engineering,BBA,BCom
