Michael Meskhi
AI Engineer at Oxy
Houston, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolMichael 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.
11 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
English, Arabic, Russian, Georgian
Stackoverflow
679reputation
82kreached
26answers
11questions
Github Skills (128)
python10
style-transfer10
deep-learning10
few-shot-learning10
representation-learning10
ml10
sql10
ai10
neural-network10
transfer-learning10
data-visualization10
database10
benchmarking10
openml10
agent10
Programming languages (14)
Github contributions (5)
MichaelMMeskhi/michaelmmeskhi
Nov 2021 - Dec 2025
Contributions:6 pushes, 1 branch in 4 years 1 month
MichaelMMeskhi/meta-learning-progress
Nov 2021 - Nov 2021
Repository to track the progress in Meta-Learning (MtL), including the datasets and the current state-of-the-art for the most common MtL problems.
Contributions:3 commits, 2 PRs, 70 pushes in 1 day
meta-learningmachine-learningdomain-adaptationtransfer-learningmeta-features
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