I'm a Computer Science graduate from Wilfrid Laurier University focused on backend systems and applied AI building services that integrate LLMs into real products, from context-aware chat backends to retrieval augmented data pipelines. I like taking a project from a rough idea to something people can actually use, I'm currently looking for full time software engineering roles where I can keep doing that.
myAIpathway Inc.
Wilfrid Laurier University
A real time platform built with FastAPI and PostgreSQL that combines a multi signal vector ranking engine with a LangChain based RAG assistant, ingesting live market data via yfinance to generate dynamic, AI driven news summaries. Redis caching cut backend overhead by 50%, and the WebSocket layer was load tested with Locust.
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An end to end machine learning pipeline built with pandas and scikit-learn to predict Canadian housing prices, reaching an R² of 0.89. Tuned Random Forest and Gradient Boosting models to minimize MAE while cutting training time by 30%, with a Streamlit interface for interactive scenario analysis.
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An English to French Seq2Seq Transformer built with TensorFlow, hitting a 27.4 BLEU score on the WMT14 dataset. Implements a full encoder decoder architecture with positional encoding, multi head attention, and teacher forcing during training.
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A real time collaborative platform with an event driven WebSocket architecture for concurrent group chat, improving user retention by 15% via sub second message delivery. A database signal driven notification engine lifted engagement by another 15%, while backend query optimizations in Django cut round trips by 20%.
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A Python chess engine with 100% FIDE rule compliance (castling, en passant, real time pin detection), using Alpha Beta pruning in a NegaMax search to cut the search space by 50% while sustaining a 3-4 ply lookahead in under a second. AI computation runs on a separate process from rendering to maintain ~60 FPS.
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