AI Intern - Applied ML & Systems Developer

Can Tho University Sep **** - Present

Information Systems (GPA: 3.15/4.0)

Motivated fourth-year Information Systems student at Can Tho University with strong interest in AI engineering and applied machine learning. Experienced in building AI-powered applications that combine Retrieval-Augmented Generation (RAG), computer vision, backend APIs, and mobile app workflows. Hands-on with Python, FastAPI, Supabase, Gemini/OpenAI APIs, YOLO, LangChain and evaluation workflows with RAGAS in end-to-end project development. Eager to contribute to real AI products, learn quickly in fast-moving environments, and grow through practical engineering challenges.

BUI XUAN DONG

********.*********@*****.*** 037-****-*** https://www.linkedin.com/in/xuandongdev/ AI TRAINEE

EDUCATION

SKILLS

Programming Languages: Python, Dart, SQL, JavaScript, basic shell scripting AI / ML: Retrieval-Augmented Generation (RAG), LangChain, prompt engineering, embeddings, semantic search, computer vision, YOLO, model evaluation with RAGAS Frameworks & Tools: FastAPI, Flutter, Supabase, Gemini API, OpenAI API, SentenceTransformers, Ultralytics YOLO, Git, GitHub, Linux, Vim

Databases & Backend: PostgreSQL / Supabase, REST APIs, relational schema design, API integration, environment configuration

Languages: Vietnamese (Native), English (Intermediate; able to read and understand technical documentation)

Soft Skills: Communication, teamwork, self-learning, adaptability, analytical thinking SUMMARY

PROJECTS

Fishy — AI Traffic Laws Assistant and Traffic Sign Recognition System Nov 2025 - Apr 2026 Github: github.com/xuandongdev/Fishy

Built an AI-powered application for Vietnamese traffic law Q&A and traffic sign recognition. Implemented a RAG pipeline with structured legal content, semantic retrieval, and LLM-based answer generation.

Used LangChain to organize retrieval and generation workflows. Applied RAGAS to evaluate answer quality and retrieval relevance. Integrated FastAPI, Supabase, and YOLO-based services into an end-to-end workflow. Designed legal-content storage in Supabase to support scalable retrieval and easier knowledge updates.

Experimented with embeddings, retrieval settings, and evaluation workflows to improve response quality.

Debugged API integration and backend service communication in a practical multi-service AI system.

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