Michael Meskhi is an AI Engineer and PhD computer scientist based in Houston with a decade of experience building production-grade machine learning systems that bridge research and industry. His doctoral work on meta-dataset distillation underpins practical strengths in meta-learning and few-shot solutions, which he has applied across multimodal RAG and LLM systems for enterprise data access and unstructured inputs. He has engineered end-to-end MLOps and cloud deployments (Docker, GCP Cloud Run, Terraform, CI/CD) and built bespoke text-to-SQL and vision-language pipelines that surface actionable insights from complex data. At Oxy he focuses on multi-agent platforms and sophisticated RAG architectures, and his background includes industry-facing projects from molecular property few-shot models to deployed ballot digitization pipelines. Known for turning theoretical advances into measurable business impact, he often combines low-data meta-learning strategies with scalable infrastructure to solve practical, high-stakes problems.
10 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Houston
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