John Cavalieri is a software engineer with a decade of experience building cloud-native, data-intensive systems, currently developing rewarded ads at Amazon in San Diego. He has a strong background in designing scalable ML and media processing pipelines—at Authenticx he helped architect a system that processed and transcribed over a million media files per day and migrated serverless workloads into Kubernetes. His earlier roles include data ingestion and ETL work in Azure and practical automation like a Teams bot to surface ETL errors, reflecting a pragmatic approach to reliability and ops. Comfortable across cloud platforms and orchestration, he combines MS and BS degrees in computer science (and a BS in mathematics) with hands-on production experience. Colleagues would describe him as someone who converts ambitious throughput requirements into maintainable systems while keeping an eye for incremental improvements.
Contributions:36 commits, 35 pushes, 1 branch in 4 days
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