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From Software Engineer to Relevance Engineer: My Personal Journey


The story began in February 2023 when I decided to switch my expertise and become a Relevance Engineer. I expressed my interest in Artificial Intelligence and asked my manager to place me on the Search and Recommendation team to follow my passion.

Even before my decision to switch my expertise, I had an interest in AI, which began during my college years. As I progressed in my career, my curiosity extended to philosophy and the power of language.


Through my journey of learning, I realized that language is the foundation of our knowledge development as humans. Our language significantly influences how we save information and knowledge.

With language, we've extended our intelligence to acquire the ability to play with fiction. We've created abstract concepts like money, companies, and even countries that don't have a tangible existence but exist in our imaginations. We call this legalized fiction, or simply put, the lies we've decided to believe together.

With language, we can communicate with computers and build incredible things in the digital world! We use programming languages to instruct computers to do what we want.

Human-Computer Interaction

As a software engineer who has spent most of my time building mobile and web applications for end-customers, I've realized that this role also involves building communication interfaces to make it easier for customers to buy what they want. Once again, it all comes down to language.

I also realized that communication between humans and computers is evolving at an exponential rate. We started with algorithms to build models to understand user behavior and provide them with the right content. Now, we have generative models like ChatGPT and MidJourney that can create many incredible things beyond our imagination.

My interest has shifted, and I want to explore the deeper understanding of how humans and computers communicate. So, I decided to refresh my knowledge of Artificial Intelligence and learn more about Natural Language Processing.

Search and Recommendation Team

In my current company, I couldn't do whatever I wanted. I needed to serve business needs while aligning them with my personal interests. Fortunately, there was a team that fit the bill: the Search and Recommendation team.

In the early stages of this team, I focused on helping with front-end work. The exciting part began when I initiated discussions with the existing team to work on the core business logic of our search feature.

I was amazed by the complexity of the problem. A search engine is not that simple. It's not just about giving customers the correct items in the SERP (Search Engine Result Page), but also about satisfying business needs. So, we're walking the tightrope between these two extremes. We're serving two masters: customers and the business.

Machine Learning?

No, I don't think the case is that complex yet, so I haven't explored machine learning extensively to solve search relevancy problem in my company. My first step is to understand how the organization achieves success with our search engine, how the search engine works, and how customers interact with the search engine to find their desired products.

However, I do anticipate exploring other problem-solving methods involving machine learning later.


This blog post is a sharing of my personal experience and may be the beginning of my journey into a new world of expertise. If you're interested in the same problem as I am, please feel free to reach out, and let's grab a cup of coffee while we discuss everything. See you!