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@huskywannacry

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Machine learning engineer focused on deep learning, production AI systems, and research-driven solutions.

Vietnam

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What I'm looking for

I seek an ML/AI role where I can build production-grade deep learning systems, work on end-to-end model deployments, and collaborate on research-driven products.

I am a machine learning engineer specializing in deep learning and production AI systems, with hands-on experience designing microservices and real-time AI applications. I combine applied research experience with product-focused engineering to deliver reliable, scalable solutions.

At Sun Asterisk I built GraphRAG-based Slack assistants and real-time voice sales chatbots using LiveKit, FastAPI, and LangGraph, emphasizing hybrid retrieval, structured reasoning, and tool-calling. In academic R&D I led the VieQA4Med dataset as first author and developed crowd-detection models deployed to live-stream camera systems.

I bring strong engineering fundamentals in Python, C/C++, and Java, familiarity with ML frameworks such as PyTorch and TensorFlow, and experience with deployment platforms like Docker and FastAPI. I seek to apply research-backed methods to production problems and contribute to teams building impactful AI products.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Engineer

Current

Sun Asterisk Inc.

May 2025 - Present (1 year 1 month)

Built an internal GraphRAG-based AI chatbot integrated with Slack and designed a microservices architecture for document ingestion, graph construction, and hybrid retrieval to provide accurate internal knowledge support. Developed a real-time voice sales chatbot using LiveKit, FastAPI, and LangGraph enabling multi-turn conversations, product inquiries, and lead qualification with tool-calling supp

Python fastAPI LiveKit LangGraph Graph RAG Microservices Docker NLP Real Time Audio

AI R&D Researcher

PTIT IEC

Jan 2024 - Jan 2025 (1 year)

Led as first author the creation of the VieQA4Med dataset through large-scale collection, cleaning, annotation validation, and preprocessing to produce high-quality medical QA pairs and contributed an academic paper. Led data collection, annotation standardization, and training/deployment of deep learning models for a real-time crowd detection system with low-latency inference.

Python PyTorch Computer Vision OpenCV data preprocessing Deep Learning

Education

Degrees, certifications, and relevant coursework

Posts and Telecommunications Institute of Technology

Engineer (Graduate of Engineer), Information Technology

2021 -

Grade: 3.42/4.0

Activities and societies: Student research and industry projects including AI/ML systems, dataset creation (VieQA4Med), real-time CV and voice chatbot development.

Graduate engineering program in Information Technology with coursework and projects focused on machine learning, deep learning, and applied AI; current GPA 3.42/4.0.