7878\end {center }
7979% -----------SUMMARY-----------
8080\section {Summary }
81- \small {ML engineer who builds AI systems end-to-end and actually tests them.
82- Shipped a complete RAG pipeline in pure Python --- custom chunker, BM25, vector
83- search, hybrid retrieval, cross-encoder re-ranking --- 87 tests, no external
84- RAG frameworks. Also built and deployed an LLM-powered ticket triage system
85- using the OpenAI API. MEng in Electrical \& Computer Engineering (University of Windsor).}
81+ \small {ML engineer who builds end-to-end AI systems and actually tests
82+ them. Shipped a production RAG service on FastAPI~+~pgvector with CI
83+ regression gating, a from-scratch RAG pipeline with MRR~1.00 and 87
84+ unit tests, and a full ML pipeline on 381K insurance records with
85+ automated data quality checks and SHAP explainability. MEng in
86+ Electrical \& Computer Engineering (University of Windsor).}
8687% -----------TECHNICAL SKILLS-----------
8788\section {Technical Skills }
8889 \begin {itemize }[leftmargin=0.15in, label={}]
@@ -109,8 +110,8 @@ \section{Projects}
109110 \resumeItem {Hybrid~+~Rerank achieved MRR~1.00 on a 25-question evaluation set,
110111 placing the correct chunk at rank~1 for every query (dense-only: 0.97,
111112 sparse-only: 0.89)}
112- \resumeItem {Validated with 87 unit tests covering chunking, retrieval, and
113- ranking; deployed on Hugging Face Spaces}
113+ \resumeItem {Validated with 87 unit tests covering chunking, retrieval, and ranking;
114+ deployed on Hugging Face Spaces}
114115 \resumeItemListEnd
115116 \resumeProjectHeading
116117 {\textbf {Insurance Re-Shopping Predictor } $ |$
@@ -125,8 +126,8 @@ \section{Projects}
125126 Test ROC-AUC 0.847 on an 88/12 imbalanced target}
126127 \resumeItemListEnd
127128 \resumeProjectHeading
128- {\textbf {RAGOps API } $ |$
129- \href {https://github.com/Archit-Konde/ragops-api }{\underline {GitHub}}}{Mar.~2026}
129+ {\textbf {RAGOps } $ |$
130+ \href {https://github.com/Archit-Konde/RAGOps }{\underline {GitHub}}}{Mar.~2026}
130131 \resumeItemListStart
131132 \resumeItem {Production-grade RAG service built with FastAPI and
132133 PostgreSQL~+~pgvector; upgrades an in-memory NumPy store to a persistent
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