Gilad Naamani is a software engineer with 11 years of experience building full-stack web applications, data pipelines, and cloud-native microservices. Currently at Google, he contributes to large-scale projects like Google Translate and cloud video analytics, leveraging Java, JavaScript, Kubernetes, Apache Beam, and BigQuery. Previously he led development of a peer-to-peer recognition platform at Betterworks and built MEAN-stack automation and an NLP clustering pipeline at Cisco, demonstrating a strong crossover between product-facing features and data engineering. He combines hands-on implementation with infrastructure tooling that materially reduced costs and sped deployments. A Computational Informatics graduate from the University of Michigan with a 3.9 GPA, he pairs rigorous academic training with pragmatic production experience. Notably, his background spans both high-scale consumer services and specialized media/data platforms, making him effective at translating complex data needs into reliable systems.
11 years of coding experience
4 years of employment as a software developer
Bachelor of Science (BS), Computational Informatics, 3.9 GPA, Bachelor of Science (BS), Computational Informatics, 3.9 GPA at University of Michigan
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