Working in Industry Research at 18

My experience as an AI research intern at a big-tech company

Ayaan Haque

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Samsung San Jose Building (Image by Author)

This summer, I had the opportunity to intern at Samsung SDSA as an AI research intern. I was part of the Artificial Intelligence team and worked on self-supervised and 3D vision problems. In this article, I’d like to share my experience working in a big-tech company as an 18-year-old and how it compared to my expectations. Moreover, I’d like to briefly discuss my project and its results. Hopefully this article is insightful for anyone curious about industry research.

Expectations

I received my formal offer pretty late in the spring, around early May. I was beyond excited primarily because I knew it would be a big step in my career. A big-tech company on my resume would open gateways to future internship and job opportunities. And best of all, I was offered a research intern position, which is what I want to do in my career.

I was expected to work 30–40 hours a week on $25/hr pay. Since I’d never been paid for my research before, I was quite happy with the rate (now, it seems relatively low compared to other big companies). While the commute was 25 minutes, I didn’t expect to be bothered by it. I’d just have to wake up around 8, which is when I woke up for school anyway.

Since I would be working 9–5 every day, I was worried about how I’d be able to do other things this summer. In preparation for college, I wanted to build my knowledge of data structures/algorithms, learn the basics of Reinforcement Learning (a goal I set out two summers ago), and review calculus. Moreover, I was concerned about when I’d be able to fit in going to the gym, playing basketball (my cardio), and hanging out with friends before moving out for college.

In terms of my expectations of work, I expected to take on an RA-style role and contribute to a larger project that the whole team was working on. During my interview, I was briefed about the team’s process. Whenever a project is requested by a customer, a few team members are assigned as leads, while the rest of the team contributes in small parts. Once papers were written, the project is handed off to the engineering team to build a product. I expected to be running experiments and writing code for the rest of the…

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Ayaan Haque

Learning about learning — EECS @ UC Berkeley— https://www.ayaanzhaque.me/ — Writer for Towards Data Science