Huiyu (Yvette) ChenMachine Learning Engineer at Meta

Hi, I’m Yvette. I build multimodal LLMs that understand content.

I’m a machine learning engineer at Meta, based in Singapore. My current work focuses on multimodal content understanding across language, images, and video—plus the training, evaluation, and production systems that make it useful.

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research brain, product hands

hello from Singapore

Now · 现在

Building multimodal content-understanding LLMs at Meta—across language, images, and video—while staying interested in the whole path from how a model learns to how a person experiences it.

Full profile ↗︎

What I do · 研究方向

Model work, systems work, and the bridge between them.

I’m happiest in the messy middle—where a promising idea has to become a reliable, measurable experience.

text · image · video

Multimodal content understanding

At Meta, I work on LLMs that understand content across language, images, and video—connecting model behavior to real product experiences.

train · evaluate · ship

Large language model systems

I care about training, alignment, evaluation, and production systems that stay measurable, efficient, and understandable at real scale.

rank · retrieve · generate

Generative recommendation

I study how retrieval, ranking, semantic IDs, and language models converge—currently documented through a twenty-paper bilingual series.

A short timeline · 简历

The current chapter,
plus just enough backstory.

details belong on LinkedIn 〰

Now

Machine Learning Engineer · Meta

Building multimodal content-understanding LLM systems across text, images, and video.

Previously

Senior Machine Learning Engineer · Shopee

Built production AI assistants for e-commerce across multiple markets. That chapter taught me how to carry an LLM idea from training to real users—without turning this homepage into a quarterly report.

Before that

Computer Science · CASIA

Research training in NLP and machine learning, with a lasting habit of reading the appendix.

Off screen

Bouldering, tennis, hiking, swimming—and too many stairs.

Still learning, still moving, still evolving.

Speaking · 演讲

One stage, one production LLM story, twenty-seven slides.

A practical talk about taking chatbot assistants from architecture decisions and model training to alignment and production scale.

Title slide for LLM-Powered Chatbot Assistants

Open 27 slides ↗︎

12 Mar 2026SingaporeML & Generative AI Stage

APAC Data Innovation Summit 2026

LLM-Powered Chatbot Assistants: Elevating the Customer Journey

I shared the system and model choices behind production-grade conversational AI—from retrieval and fine-tuning to alignment, evaluation, and deployment.

View the slides LinkedIn highlight

Topics · 专题入口