Available for Co-op · 2026

MD Saif Aldeen

4th-year CS @ University of Calgary  /  Software Engineering · Co-op Program

I'm a 4th-year CS student at UCalgary building full-stack and ML projects in my free time. Currently hunting for co-op opportunities where I can ship real code and learn from experienced engineers.

// student stats

4th
Year
5+
Projects
6
Languages
$5k
Scholarship
SA

About Me

I'm a 4th-year Computer Science student at the University of Calgary specializing in Software Engineering, enrolled in the Science Co-op program. I build full-stack applications, ML pipelines, and REST APIs — and I care about writing code that actually works in production, not just on my machine.

My experience spans IT support at Geek Squad, an AV/IT co-op at UCalgary, and leading operations for the Deep Racer Club where we train and race autonomous vehicles on AWS. I'm actively looking for a software engineering or data internship where I can contribute from day one.

🎓
University of Calgary BSc Computer Science, Alberta, Canada
💻
Software Engineering Concentration Science Co-op & Internship Program
🏆
President's Award · $5,000 Scholarship for outstanding academic performance
📍
Calgary, Alberta Open to remote & hybrid co-op roles
📅
Expected Graduation April 2027

Tech Skills

Python90%
Java82%
React / TypeScript75%
C / C++70%
ML / PyTorch / XGBoost72%
SQL / Databases78%
Docker / GitHub Actions68%
Linux / Bash80%
LangChain FastAPI FAISS Streamlit Node.js Django .NET 6 Pandas pytest AWS (basic) Power BI SMOTE
Python· Java· React· FastAPI· LangChain· PyTorch· Docker· SQL· Node.js· FAISS· XGBoost· AWS· Linux· Git· C#/.NET· Python· Java· React· FastAPI· LangChain· PyTorch· Docker· SQL· Node.js· FAISS· XGBoost· AWS· Linux· Git· C#/.NET·

Recent Projects

Jan 2026 – Present

ChatPDF: RAG Web App

Upload any PDF and ask questions in plain English. Answers are grounded in the document; nothing is hallucinated.

  • FastAPI backend with 4 REST endpoints: upload, query, list, delete
  • Full RAG pipeline: LangChain for PDF chunking, FAISS for semantic search, Groq LLaMA for grounded generation
  • Multi-PDF support + Finance Mode with pre-built shortcuts for earnings reports, risk extraction, and financial figures
  • 17 pytest unit tests covering all endpoints including edge cases
Python FastAPI LangChain FAISS Groq LLaMA pytest
April 2026

Financial Fraud Detection System

End-to-end ML fraud detection pipeline on 100,000 PaySim transactions, deployed as an interactive Streamlit dashboard with real-time risk scoring.

  • Handled 1.3% class imbalance using SMOTE; XGBoost hit AUC-ROC 1.0 on held-out test set
  • Compared three approaches: Isolation Forest (anomaly), XGBoost (gradient boosting), PyTorch LSTM (sequential patterns)
  • Interactive Streamlit dashboard for real-time transaction risk scoring
Python XGBoost PyTorch LSTM SMOTE Streamlit Pandas
In Progress

PDG Builder

A program dependency graph builder for static analysis; parses source code and visualizes data and control flow dependencies between statements.

  • Parses source code into structured dependency nodes and edges
  • Visualizes control flow and data flow for static analysis use cases
  • Relevant for compiler optimization research and code quality tooling
Python Static Analysis Graph Theory

Experience & Leadership

Oct 2024 – Present
IT Support Technician
Geek Squad | Best Buy
  • Manage front-desk operations; triage inquiries and route to the right services
  • Diagnose and resolve Windows/Linux, networking, and hardware issues
  • Track 200+ cases in CRM with clear handoffs and knowledge base write-ups to prevent repeat escalations
April 2024 – September 2024
AV/IT Operations, Summer Co-op
University of Calgary
  • Maintained AV/IT systems for uninterrupted operation during university events and conferences
  • Minimized downtime by identifying and resolving technical issues in IT infrastructure
  • Applied systematic troubleshooting, analytical problem-solving, and proactive maintenance strategies
Sep 2023 – Present
Operations Executive
Deep Racer Club | UCalgary
  • Manage operations for autonomous car events; download, test, and fine-tune ML models so cars navigate tracks correctly
  • Train Python-based ML models on AWS; handle dataset prep and experiment runs
  • Cataloged 50+ items, coordinated volunteers, demonstrating ownership, communication, and follow-through

Get In Touch