This article is part of #GiveToGain, Tech in Asia’s 2026 International Women’s Day campaign.
Over the past year or so, you may have seen a number of new AI-powered features and formats on Tech in Asia. From news summaries on social media to additional “food for thought” segments appended to articles, these features are a reality thanks to the efforts of our data and engineering team.
Yeo Cheng Yong, machine learning engineer at Tech in Asia / Photo credit: Tech in Asia
Yeo Cheng Yong is a member of that dedicated squad, serving as a machine learning engineer helping tackle the nitty-gritty details involved with AI innovation. In this interview, she tells us more about how she landed in the world of data and engineering, navigating life as a working parent, and how we can better support women in the workforce.
The following interview has been edited for clarity and brevity.
For the benefit of our readers, what do you do at Tech in Asia?
I work as a machine learning engineer at Tech in Asia. In my role, I help the company build new features in our product using AI, machine learning, and data engineering.
How did you arrive at this point in your career? What was the journey like, and what were some pivotal moments?
When I was applying for university, I chose to study mathematics simply because I enjoyed it and it opened up a lot of different career paths. After graduation, I joined Micron Technology as a production planning engineer. There, I became interested in machine learning and took online courses in my free time to upskill myself.
The pivotal moment came when the directors at Micron asked me to join a pilot team responsible for building big data applications. That’s when my interest transformed into my full-time role, and I haven’t looked back since.
What is your biggest achievement at Tech in Asia?
Building a feature called “Go Deeper.” This feature enabled users to explore topics discussed in our articles more thoroughly and was released publicly in early 2025.
I built a production-scale system that encompassed search and retrieval from our own content, web scraping from external data sources, and the use of LLMs and agentic workflows to generate high-quality answers.
At a time when most companies were still figuring out how to use AI in production, I was invited to share about this project at a DataScienceSG meetup, where there were many questions from the floor about improving answer quality while reducing latency and managing costs.
Presenting on Go Deeper / Photo credit: Cheng Yong Yeo
“Go Deeper” has since been sunsetted, due to a lack of product-market fit and high costs involved, but it taught us a great deal about using AI in media and has helped shape Tech in Asia’s direction in AI development.
What about the biggest challenge you’ve faced in your career? How did you overcome it?
Do you think the tech industry has done enough to promote gender diversity and empower women?
Who is your female hero or inspiration? Why?
What is the best advice you’ve ever received?
On the flip side, what is one piece of advice you’d pass down to other women looking to get into the tech space?
The theme for this year’s International Women’s Day is “Give to Gain.” What does this mean to you, and how do you intend to give to gain?
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