Muhammadmoiz User

I’m a Senior Data Scientist with nine years of progressive experience designing, building, and deploying machine learning, deep learning, and Generative AI systems at production scale. I lead end-to-end ML lifecycles—from data engineering and model development to MLOps and LLMOps deployment and monitoring—across fintech, enterprise, and healthcare-adjacent environments.

I’m hands-on with LangChain and LangGraph, Retrieval-Augmented Generation (RAG), large language models, and natural language processing, and I build cloud-native ML pipelines on AWS and Azure. I focus on turning ambiguous requirements into scalable AI solutions through strong cross-functional collaboration and consistent technical mentorship.

In my current role, I lead the design and deployment of Generative AI solutions, orchestrating multi-step agentic workflows with LangChain and LangGraph. I’ve architected RAG pipelines using FAISS and Pinecone, improving response relevance by approximately 35% over baseline keyword search, and I’ve built end-to-end MLOps and LLMOps pipelines on AWS and Azure, cutting average release cycle time from two weeks to three days.

I also deliver domain-focused NLP, including HIPAA-aware clinical and healthcare-adjacent document processing with 90% extraction accuracy, and I apply prompt engineering and fine-tuning to reduce hallucination in production. Previously, I improved deployment reliability by 40% and reduced production incidents by ~35% while documenting and standardizing processes across 15+ projects—so I’m now ready to bring deep technical leadership and applied AI expertise to a high-growth, globally allocated team.