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Computer Science and Applied Mathematics student at the University of Toronto with strong experience building AI-driven full-stack and data engineering systems. Passionate about transforming raw data into reliable pipelines, shipping production features, and applying ML techniques to real-world problems. Experience spans backend API development, RAG-based tutoring applications, and production-grade data quality and lineage services. Committed to testing, automation, and collaborative development through peer-reviewed PRs and CI/CD.…Computer Science and Applied Mathematics student at the University of Toronto with strong experience building AI-driven full-stack and data engineering systems. Passionate about transforming raw data into reliable pipelines, shipping production features, and applying ML techniques to real-world problems. Experience spans backend API development, RAG-based tutoring applications, and production-grade data quality and lineage services. Committed to testing, automation, and collaborative development through peer-reviewed PRs and CI/CD.

NGUYEN VO KHOI NGUYEN

Programmer, Web Developer, Back-End Developer, +2

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Computer Science and Applied Mathematics student at the University of Toronto with strong experience building AI-driven full-stack and data engineering systems. Passionate about transforming raw data into reliable pipelines, shipping production features, and applying ML techniques to real-world problems. Experience spans backend API development, RAG-based tutoring applications, and production-grade data quality and lineage services. Committed to testing, automation, and collaborative development through peer-reviewed PRs and CI/CD.…Computer Science and Applied Mathematics student at the University of Toronto with strong experience building AI-driven full-stack and data engineering systems. Passionate about transforming raw data into reliable pipelines, shipping production features, and applying ML techniques to real-world problems. Experience spans backend API development, RAG-based tutoring applications, and production-grade data quality and lineage services. Committed to testing, automation, and collaborative development through peer-reviewed PRs and CI/CD.

Available to hire

Computer Science and Applied Mathematics student at the University of Toronto with strong experience building AI-driven full-stack and data engineering systems. Passionate about transforming raw data into reliable pipelines, shipping production features, and applying ML techniques to real-world problems.

Experience spans backend API development, RAG-based tutoring applications, and production-grade data quality and lineage services. Committed to testing, automation, and collaborative development through peer-reviewed PRs and CI/CD.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Language

Work Experience

Student Software Engineer at University of Toronto Mississauga

September 1, 2025 - December 31, 2025

Led development of an AI tutoring platform used by 200+ computer-architecture students. Integrated a fine-tuned RAG chatbot with an automated quiz-generation and validation pipeline. Owned full-stack integration: built interactive datapath visualizations in Next.js/React and designed a Django API layer that transformed raw processor execution traces into structured JSON in real time.

Undergraduate Teaching Assistant at University of Toronto — Department of Mathematical & Computational Sciences

September 1, 2024 - June 30, 2026

Led tutorials, office hours, and review sessions, translating complex algorithms and mathematical concepts into structured technical explanations. Supported 200+ students across seven computer science and mathematics courses including data structures, computer organization, theory of computation, and algebraic cryptography.

Data Engineer Intern at GHN (Giao Hang Nhanh)

May 1, 2024 - August 31, 2024

Built automated data-quality checks with Airflow to scan 30K+ rows per run and detect missing/invalid records, improving pipeline reliability. Developed a production Python service that transformed SQL table dependencies into structured data across 1,300+ tables and 200 Airflow DAGs, reducing root-cause investigation time by 60%. Refactored data-processing services from Postgres workflows to PySpark to reduce latency by 20% and improve maintainability. Automated an Airflow permissions ingestion pipeline, eliminating 150 hours of annual cross-team communication across seven teams. Delivered tested production features using peer-reviewed pull requests and GitHub Actions CI/CD.