MLOps, Data Engineer, Devops

Vo Trong Nhon

MLOps / DevOps / Data Engineering AI Systems Integration

097*******

Ho Chi Minh, Viet Nam

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Career Summary

Engineer at the intersection of AI and systems: building MLOps / DevOps / Data Engineering pipelines from data ingestion and feature engineering to model training, deployment, and observability. Strong interest in AI-driven optimization for production systems. Seeking an Intern role to contribute to cloud-native ML platforms, automation, and scalable data workflows.

Education

Industrial University of Ho Chi Minh City Aug 2022 — Present Bachelor of Science in Data Science GPA: 3.55/4.0

Projects

MLOps System for NYC Taxi Demand Forecasting 08/2025 – Present Role: MLOps Engineer Tools: MLflow, Docker, FastAPI, Airflow, Grafana, Prometheus Github

• Designed and implemented a complete MLOps pipeline for 15-minute taxi demand forecasting on NYC TLC data (2015–2025).

• Developed automated ETL pipeline with DuckDB and Airflow: data cleaning, feature extraction (30+ temporal, lag, cyclical, and weather-based features).

• Trained and evaluated Poisson/Tweedie regression models using LightGBM and XGBoost with Out-of-Time cross-validation (2020–2024).

• Containerized model service with FastAPI + Docker Compose, integrated MLflow for experiment tracking and model registry (DagsHub).

• Implemented automated retraining every 6 hours and continuous monitoring via Prometheus, Grafana, and Evidently AI for drift detection.

• Set up CI/CD pipeline with GitHub Actions and unit testing (53 tests, 88.7% pass rate) to ensure reproducible deployment.

Customer Propensity to Purchase (Dockerized Pipeline) 02/2024 – 05/2024 Role: Data Engineer Tools: Python, Airflow, Docker, Pandas Github

• Built a containerized data pipeline to analyze and predict customer purchase propensity using historical transaction data.

• Orchestrated ETL tasks with Apache Airflow, modularized data cleaning and feature engineering processes.

• Applied ML models for binary classification and evaluated performance using AUC and F1 metrics.

• Packaged environment reproducibly with Docker for portable deployment and testing. Multimodal Sarcasm Detection (UIT Challenge 2024) 08/2024 – 09/2024 Role: AI Engineer Tools: PyTorch, ViT, VinTern, Jina Embeddings, Focal Loss Github

• Developed a multimodal classification pipeline for sarcasm detection using text, image, and caption features.

• Integrated VinTern-1B-v2 for visual captioning and ViT + Jina Embeddings for text-image alignment.

• Implemented ensemble models with Cross-Entropy and Focal losses; achieved Top-1 leaderboard result (F1 = 44.75%).

Mori_Cloud 03/2025 – 05/2025

Role: Full-stack Developer Tools: Python, Flask, HTML/CSS/JS, OpenCV Github

• Developed an AI-powered web application to store and search personal memories via semantic image retrieval.

• Implemented secure authentication and metadata-based image search using facial embedding extraction with OpenCV.

• Deployed full-stack app on local containerized environment with Docker. RESEARCH PROJECTS

1.

ViAMR: Fine-tuning LLMs for Abstract Meaning Representation in Vietnamese

Github

VLSP 2025 (Accepted)

*Dien X. Tran, *Nhon V. Trong, Kien C. Nguyen

HONORS & AWARDS

1. VLSP 2025 Evaluation Campaign 2025

a) Top 2 – Semantic Parsing

b) Top 6 – Numerical Reasoning QA

2. UIT Challenge 2023 – 2024

a) First Prize – UIT Challenge 2024

Technical Skills

• MLOps & DevOps: MLflow (DagsHub), Docker, Airflow, FastAPI, Prometheus, Grafana, GitHub Actions (CI/CD).

• Data Engineering: SQLServer, Pandas, DuckDB, Feature Engineering, Power BI.

• Machine Learning: Scikit-learn, LightGBM, XGBoost, TensorFlow, PyTorch.

• Languages: Python, SQL, HTML/CSS/JS.

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