Turning Complex Data Science into Production-Grade Software.
I am a Solutions Engineer with a dual background in Applied Statistics and Computer Science. My expertise lies in the “messy middle” of modern tech: taking a theoretical model or a raw business need and engineering a robust, scalable, and cost-effective production system around it.
Whether it’s fine-tuning Llama 3 on a budget or architecting an event-driven AWS backend that scales to zero, I build software that solves business problems.
🛠️ Technical Arsenal
| Domain | Key Technologies |
|---|---|
| AI & LLM Engineering | Llama 3.2 (Fine-tuning), LoRA/UnslothAI, RAG Pipelines, spaCy, BERTopic |
| Cloud Architecture | AWS Serverless (Lambda, DynamoDB Streams, API Gateway), CloudFormation (IaC) |
| Backend & DevOps | Python (FastAPI/Django), Docker, GitHub Actions CI/CD, PostgreSQL |
| Data Engineering | ETL Pipelines, Web Scraping (Selenium), Visual Analytics (Dash/Plotly) |
🚀 Featured Engineering
01. AI-Powered Mindful Eating Companion
Generative AI & Mobile Engineering
The Challenge: Generic health apps lack context. I needed a system that could “read” user personality and adapt its advice dynamically.
- The Engineering: Fine-tuned two Meta Llama 3.2 (3B) models using LoRA adapters. Built a proprietary dataset of 1,500 expert-verified tips to ensure clinical safety.
- The Impact: Achieved ~88% relevance in user-rated pilot tests, running effectively on consumer-grade hardware.
02. SecureTask: Serverless Identity Verification
Cloud Architecture & Security
The Challenge: Building a secure biometric task platform without the operational overhead and cost of managing GPU servers.
- The Engineering: Architected a fully serverless AWS stack. Integrated Rekognition for face-ID (Selfie vs. ID) and used CloudFormation to deploy the infrastructure in <5 minutes.
- The Impact: Reduced infrastructure costs by ~40% compared to legacy containerized solutions.
03. Public Tenders Intelligence Dashboard
Data Engineering & Visual Analytics
The Challenge: Procurement analysts were losing hours manually digging through 10 years of unstructured government tender data.
- The Engineering: Built an automated ETL pipeline to clean data noise by 35% and applied BERTopic (NLP) to surface hidden spending trends automatically.
- The Impact: Accelerated trend identification speed by 30%, transforming raw CSVs into strategic intelligence.
🧩 Off the Clock
My downtime usually looks a lot like my work: analyzing systems. Whether I’m optimizing character builds in an RPG or dissecting the plot structure of a slow-burn thriller, I enjoy figuring out how things work.
- Gaming & Cinema: I’m drawn to deep lore and complex mechanics. Favorites include The Witcher 3 and Better Call Saul.
- Background Process: Powered almost entirely by black coffee.
Let’s Build Something Scalable
Current Status: Based in Halifax, NS. Open To: Roles in AI Engineering, Backend Development, and Cloud Architecture.