Work Experience
Build and optimize distributed LLM post-training systems, accelerate research iteration, and develop tooling for science experiments.
Led ML projects addressing marketplace problems, owning the work from problem framing through model development, experimentation, and production serving.
Career Transition
In my first two years of undergraduate studies, I wanted to know how the world works and wanted to build a solid analytical mindset, which led to my Economics major. Having that foundation, I went to business school to study how businesses operate, how to manage employees, how to raise capital in the financial market, how to market a product and other related business subjects. Our business courses were all taught using case-studies, which is a risk-free way to become a strategic decision-maker.
Time was a major constraint, in pursuing my childhood passion on the side. I developed a passion for computers from my parents’ influence as software developers in the 90s. Memories such as playing Cyberdogs with my dad in DOS or publishing my first HTML webpage on GeoCities still vividly linger in my head.
After a year studying Business, I realized that simply analyzing different companies and products wasn't enough for me, I wanted to be part of creating the product, which led to me switching into Computer Science. Computer Science wasn't about programming, rather it was about finding patterns, developing efficient solutions given numerous constraints, and being able to think abstractly to generalize solutions.
I haven't, for a second, regretted my decision. These unique experiences define who I am. My computer science background enhanced my problem solving abilities. My business and economics background provided me with an acumen for seeing the bigger picture and a mentality to derive implication from facts.
I would like to thank all of my friends' and mentors' support along the way. Without them, I wouldn't have come this far.