Vietnamese LLM fine-tuning pipeline
End-to-end flow from collection and cleaning through LoRA training to automated evaluation, reproducible with one command.
-> experiment cycle: 9 days -> 14 hours
$ whoami
Truong Duc Dung - AI Engineer. I take models out of the notebook and into production.
I focus on LLM systems that can run in production: RAG over internal data, Vietnamese model fine-tuning, inference infrastructure, and quality evaluation before product rollout. I write up what I learn in the blog below.
$ ls ./work --selected
04Internal document assistant
Question answering over 180,000 pages of a bank's procedures and contracts, with source citations and per-department access control.
-> 62% less time spent on manual lookup
Real-time transaction risk scoring
Gradient boosting model served under 40ms p99, with drift monitoring and automatic rollback.
-> 1.4M inferences per day
eval-kit - open source evaluation library
A small toolkit for testing LLM output the way you write unit tests, used internally before it was open sourced.
-> 1,900 github stars, 40 contributors
$ cat experience.log
2023 - now
AI Engineer
Fintech product company, Hanoi
Leading a team of four building the internal LLM platform and the applications on top of it.
2021 - 2023
Machine Learning Engineer
E-commerce startup
Recommendation and inventory forecasting systems for 2M monthly active users.
2019 - 2021
Data Scientist
Data consultancy
Demand forecasting and customer segmentation models for retail and logistics clients.
$ cat stack.toml
[models]
pytorchtransformerslora/qlorarageval & benchmarkdistillation
[infra]
vllmtritonkubernetesrayairflowawsterraform
[languages]
pythongosqlduckdbpostgres/pgvectorweights & biases
$ ls ./blog
all posts ->~/contact.sh
Got an AI problem that needs to ship?
I take on architecture reviews, prototypes, and hands-on work until the system runs for real. Send a few lines of context; I reply within 48 hours.