Senior AI Engineer with 10+ years of progressive experience spanning cutting-edge AI development, machine learning research, and enterprise data analytics. Currently architecting scalable GCP-based RAG systems and multi-agent AI solutions at SQOR.ai, while holding a Master's in Applied Data Science from San Jose State University.
I specialize in Generative AI, Agentic RAG architectures, and Large Language Model Operations (LLMOps), having deployed 13 specialized AI agents and pioneered proprietary semantic chunking algorithms that significantly improved data retrieval accuracy. My expertise spans the complete AI/ML lifecycle—from research and development to production deployment and optimization.
My unique blend of cutting-edge AI innovation and business acumen has consistently delivered measurable impact: from developing Edge AI systems with 90.71% model compression for IoT deployment to achieving 34% increase in business metrics through advanced analytics. I excel at translating complex AI concepts into production-ready solutions that drive real business value.
With published research in IEEE journals and international conferences, including breakthrough work on deep learning for healthcare applications and novel oversampling techniques, I bring both theoretical depth and practical implementation expertise to AI challenges across healthcare, finance, and emerging technologies.
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