My Journey into Tech: Machine Learning Engineer, Win Suen's Perspective
I took an unconventional (but fun!) route into engineering. I was a humanities major in college, with a focus on archival research and 15th-century Venetian diplomatic manuscripts - not the typical background for someone in tech. After graduation, I joined an ed tech startup, which got my foot in the door in the industry. In those first couple of years, I definitely learned a lot by doing.
During that time, I discovered my love for solving hard technical problems. There is something thrilling about looking at a new problem that you have no idea how to solve in the beginning and having the chance to develop a novel solution. I taught myself Python from books and by working on side projects. Eventually, I transitioned to building anti-fraud data science applications at a previous employer.
In 2019, I joined Dropbox as a Machine Learning Engineer. Day-to-day, I work with some of the smartest engineers, designers, and product leaders I know to develop new ML-powered recommendations and retrieval features for our users. I learn new things every day, and that's one of the things I love most about Dropbox's engineering culture.
When I decided to work for Dropbox, I considered three things: exciting new challenges as the company grows into a new space, a strong engineering culture, and the people. With the new directions Dropbox is taking into AI/ML, there are interesting machine learning problems for existing and new products. Not only that, but Dropbox has a robust engineering culture with an emphasis on shipping great products. On top of that, I work with an exceptional group of people from whom who I can learn and grow. Throughout my years at the company, my peers have taught me so much that I could not have learned elsewhere.
Dropbox has had a huge positive impact on my professional journey. From day one, I have been consistently impressed with Dropbox's engineering teams. The amount of thought put into making the onboarding process effective really makes a difference. Thanks to the support and mentorship from fellow Dropboxers, I was committing feature code within a week of starting - that's a testament to how much care is put into ensuring new engineers can start contributing early. Now as a senior engineer, biasing for impact means shifting to setting others on your team up for success, in addition to continuing work of technical excellence.
And it doesn't end there. Dropbox is very impact-driven, giving engineers many opportunities and challenges that stretch their abilities. I have never worked on a project that hasn't taught me something new, and I learn many things that I can share with others or take on into future work. For example, in recent research into how to safely leverage LLMs for retrieval problems, there was a moment when I looked at the latest open-source software, models, and deployment frameworks -many of the newest technologies out there hadn’t been made widely available yet. All of the tools were novel, and it felt great to be able to learn and have an impact in such an immediate way.
As I've grown at Dropbox, I have also found opportunities to be a mentor myself. I've enjoyed working with junior engineers as part of the Dropbox internship program. As an intern mentor, my role is to develop and guide my mentee through developing and deploying an impactful real-world ML application at Dropbox. Our internship program is very hands-on, and it is very rewarding to be able to help others early on in their careers, as others once helped me.
Dropbox's culture of growth and career development shows up across teams. I show up every day knowing I will learn something new — I try not to take that for granted!
