AI/ML Engineer (PyTorch, TensorFlow)

Experienced in PyTorch, TensorFlow, and real-world AI integration (docker, API, deployment). Familiar with data labeling, cleaning, and training/evaluating models for both CV and NLP. Eager to research and implement state-of-the- art AI under guidance

ABOUT ME

SKILLS

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TRINH DUC THIEN

github.com/tdthien106

EXPERIENCE

Data labeling - Alchera

Ensured high-quality image annotation by drawing precise bounding boxes and aligning LiDAR data with objects across each frame

Maintained strict quality standards, achieving a processing speed of 4–6 images per hour with high consistency

IT Support - IIG

Performed computer setup, software installation, and troubleshooting for candidates taking exams at IIG.

Conducted pre-exam system checks and resolved technical issues on-site to ensure smooth exam delivery

PROJECTS

Thesis - Reconstructing images from brain waves Grade: 9.2/10 Implemented IC-GAN (Inversion-based Conditional GAN) to optimize latent variables, aiming to enhance the quality of reconstructed images from brain wave signals. Improved output image fidelity by fine-tuning latent space representations, resulting in more accurate and visually coherent reconstructions.

Software - Coffee shop - Grade: 8.6/10

Full-stack dev: Built React.js/Vite frontend with Tailwind CSS, PostgreSQL database, and Docker containerization (reduced setup time by 40%).

QA automation: Implemented TDD with 20+ test cases, automated E2E/UI testing using Katalon

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Deployment: Deployed frontend to Vercel for high availability and performance. EDUCATION

University of Science Information technology

Programming: Python, C/C++, JS

AI/ML frameworks: PyTorch, TensorFlow, Keras

NLP & CV: transformers, tokenizers, datasets, nltk, spacy, opencv Data & MLOps: pandas, numpy, scikit learn, streamlit System integration: Docker, PostgreSQL, REST API, Vercel, Katalon English: B1 (reading technical documents & research papers) AI ENGINEER INTERN

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