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About the Role
- Implement ETL pipelines in Azure cloud environment for reporting and analytics projects
- Monitor and support existing BAU pipelines in Azure cloud platform
Provide infrastructure support to Azure cloud platform users as a part of the admin team
Roles and Responsibilities :
Design and implement MLOPS, i.e. set of tools and operating models used to deploy and maintain machine learning models in production reliably and efficientlyAct as a bridge between data scientists and IT & data engineers & data architects, especially during development & production architecture design & set-upTest and optimizing machine learning models and algorithms before they go in productionAssist in monitoring and retraining models when neededMinimum Job Requirements :
Degree in computer science, math, statistics or relatedStrong knowledge and experience in PythonStrong knowledge and experience in MLOPSStrong communication skills in English, both spoken and writtenStrong knowledge and experience in machine learning and statisticsStrong Software engineering skillsGood knowledge of Agile, DevOps, TDD, CI / CD tools & methodologiesFamiliar with Azure Databricks, MLFLOW, Dockers, KubernetesFamiliar with DB / Cache systems like SQL Server, MongoDB, Redis, etc.Strong analytical, problem-solving and teamwork skills3+ years of relevant experienceNice to Have :
Good knowledge of Microsoft Azure stack (AMLS, Synapse, Data Factory, etc.)Strong knowledge of DatabricksStrong knowledge of pySpark & SQLStrong experience in Python web framework like Flask, Django, FastAPI, etc.Strong knowledge of RDBMS and 2+ NoSQL database