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Thursday September 4, 2025 9:30am - 9:55am PDT
Aditi Jain, Amazon SDE
Bhavani Sankar Telaprolu, Google, Software Engineer


As AI/ML adoption accelerates across industries, many teams face critical challenges in bringing models from prototype to production—especially in cloud environments. This session explores how MLOps practices, automation, and cloud-native tools can streamline the deployment and monitoring of both traditional ML and emerging GenAI models. Attendees will learn how to structure ML pipelines, manage data and model versioning, implement CI/CD for ML, and optimize cloud costs, all while ensuring reproducibility and governance. Drawing on real-world experiences, this talk offers actionable insights for making ML systems robust, scalable, and production-ready in the cloud.  
Speakers
avatar for Aditi Jain

Aditi Jain

SDE, Amazon
As an experienced software developer and AI specialist, I've dedicated my career to implementing cutting-edge technologies across various platforms. My journey, spanning both industry and academia, has given me a unique perspective on the challenges and opportunities of deploying... Read More →
avatar for Bhavani Sankar Telaprolu

Bhavani Sankar Telaprolu

Software Engineer, Google
Bhavani Sankar Telaprolu is a seasoned Cloud and AI Solutions Architect with over 5 years of experience designing and deploying scalable machine learning systems in the cloud. He specializes in MLOps, cloud-native architecture, and productionizing generative AI models. Bhavani has... Read More →
Thursday September 4, 2025 9:30am - 9:55am PDT
CloudX -- Main Stage

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