Building intelligent systems that extract signal from noise — from RAG pipelines over 1,200+ document chunks to ML models with measurable performance gains. Research-backed, production-oriented.
I'm an AI/ML Engineer with hands-on research and industry experience spanning data preprocessing, model evaluation, and end-to-end pipeline development. My work sits at the intersection of machine learning engineering and applied research.
From reducing preprocessing time by 38% at DeepQore to building a RAG system achieving 87% top-5 retrieval accuracy, I consistently translate research insights into measurable engineering outcomes.
I've worked across AI + neuroscience research at GBSCIDP & NeuroAI Research Foundation, giving me a broad perspective on how intelligent systems can push disciplinary boundaries.
A full-stack AI engineering toolkit spanning languages, frameworks, data infrastructure, and research methods.
Three research and industry roles spanning data engineering, model optimization, and AI/neuroscience research.
Four end-to-end AI/ML systems demonstrating research depth and production-level engineering capability.
End-to-end RAG pipeline built over 1,200+ document chunks. Implements PDF ingestion, semantic chunking, embedding generation, and hybrid search combining vector similarity with metadata filtering. Redis caching layer reduces response latency significantly.
Movie recommendation engine built on a 5,327-title dataset. Uses TF-IDF vectorization on metadata and cosine similarity for real-time matching. Sub-100ms response times make it suitable for production integration.
Controlled generative AI application leveraging large language models with structured prompt engineering. Optimized prompt templates guide output coherence, style, and length. Deployed as an interactive Streamlit app.
Full ML pipeline for academic outcome prediction on a 1,001-record dataset. Systematic feature engineering, preprocessing, and model selection lifted accuracy from 0.71 to 0.80 — a 12.7% relative improvement.
Industry-recognized certifications validating core ML, data science, and AI competencies.
Full PDF resume with detailed experience, education, and project documentation — ready for recruiter review.
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