Job Description
A Snapshot of Your Day
The day of an ML Developer/MLOps Engineer starts the day by reviewing model performance metrics and identifying any drift in production models. A team meeting follows, where updates on model training and evaluation pipelines are shared. The engineer then works on converting Jupyter notebooks into reproducible training pipelines, ensuring proper version control. After lunch, they package and serve a new machine learning model via Azure ML Endpoints, collaborating with data engineers to manage data and feature pipelines. The day concludes with documenting the integration process and planning for improvements based on stakeholder feedback.
Bridge the gap between data science and production: package models into reliable, secure, and scalable AI applications on Azure, with a focus on automation, observability, and operational excellence.
How You'll Make An Impact
Build, deploy, and operate AI applications as production-grade microservices on Azure (App Ser...
The day of an ML Developer/MLOps Engineer starts the day by reviewing model performance metrics and identifying any drift in production models. A team meeting follows, where updates on model training and evaluation pipelines are shared. The engineer then works on converting Jupyter notebooks into reproducible training pipelines, ensuring proper version control. After lunch, they package and serve a new machine learning model via Azure ML Endpoints, collaborating with data engineers to manage data and feature pipelines. The day concludes with documenting the integration process and planning for improvements based on stakeholder feedback.
Bridge the gap between data science and production: package models into reliable, secure, and scalable AI applications on Azure, with a focus on automation, observability, and operational excellence.
How You'll Make An Impact
Build, deploy, and operate AI applications as production-grade microservices on Azure (App Ser...
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