Applied AI Engineer focused on LLM systems, APIs, and backend development
Wilfrid Laurier CS & UX grad · Humber AI & ML postgrad · Incoming MSc Artificial Intelligence student at the University of Liverpool
Previously worked across AI systems, data, analytics, and internal tools through roles at Arrowz, the Ontario Ministry of Education, DPCDSB, and Meter
- LLM Memory & Agent Systems - persistent memory, retrieval logic, long-term context, and practical AI workflows
- Multimodal AI & VLMs - combining vision and language for useful tools and interfaces
- Model Optimization - fine-tuning, quantization, and efficient inference
- Applied ML Systems - recommender systems, prediction pipelines, and end-to-end deployment workflows
- Game Development - building games and interactive systems in Unreal Engine 5
Languages:
Python · TypeScript · SQL · Go · Julia · Java · C# · R · Dart
AI Systems & LLMs:
LLM Pipelines · Prompt Engineering · Conversational Memory Systems · Model Integration · Hugging Face · LangChain
Machine Learning & AI:
PyTorch · Scikit-learn · TensorFlow · Apache Spark · OpenCV · Vision-Language Models (VLMs)
Backend & APIs:
FastAPI · Flask · REST APIs
Cloud & Data:
AWS (EC2, S3, SageMaker) · PostgreSQL · MongoDB
Additional Tools:
Flutter · React · Tableau · Figma
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LLM + GNN Integration for Renewable Energy
Industry-sponsored capstone combining LLMs with MoFlow and DimeNet++ for molecular generation and property prediction -
CooperLM-354M
Trained a custom 354M parameter GPT-style language model using the Hugging Face ecosystem -
Context-Aware Anime Recommender
Built a Transformer-based recommender with personalized feedback and explainable outputs -
Salary Predictor - Multi-Language ML Pipeline
Built a cross-language ML system using Julia, Go, Python, Bash, and SQLite
