Hey! My name is Gerardo and I’m a data science major at the Monterrey Institute of Technology and Higher Education in Mexico. I’m deeply passionate about the interplay of mathematics and coding, which is why I chose to major in data science. I have had my sights set on a career in the Natural Language Processing (NLP) field for a while now, and recent advancements made by large language models like ChatGPT have opened up new opportunities, sparking my interest even more.
I first heard about the Major League Hacking (MLH) Fellowship when a previous MLH Fellow shared their experience with me. I participated in the Software Engineering track in Spring 2023 and I have to say it couldn’t have been a better choice!
Make an Immediate Impact
During the MLH Fellowship, I had the unique opportunity to collaborate alongside the bright minds at Meta AI, Meta’s premier artificial intelligence research department. The fascinating field of artificial intelligence, especially natural language processing and language models, is where I’ve found a stimulating learning and working environment.
My typical day as an MLH Fellow involved a deep dive into understanding the mechanics of the features I was assigned to integrate, followed by the coding phase. With Meta, I contributed to their language model repositories and was deeply involved in implementing features derived from AI literature, particularly those concerning the state-of-the-art transformer architecture (the engine behind GPT models).
Learn Practical, Real World Skills
I would say my learning in the MLH Fellowship could be distilled into three main areas. First, I learned what’s necessary to build and maintain a Python library. These technical skills in Python standards and best practices have been indispensable in ensuring the quality of my subsequent projects.
Second, aside from learning the nuances of maintaining a Python library, the MLH Fellowship taught me the invaluable skill of becoming an effective open-source citizen. Understanding the norms of contributing to open-source projects is an important part of modern software development.
And finally, I learned about the actual algorithms and features that make their generative pre-trained transformer (GPT) so state-of-the-art. This part fascinated me the most! The features that I contributed to that integrate into our models are the same ones that big tech companies are using in their large language models. For example, recently I came across a paper on a new language model by MosaicML (MPT). I was excited to see that ALIBI, a masking technique that I had integrated for Meta during my fellowship, was among the key features that made the new MPT model a game-changer.
Build an Incredible Network
The MLH Fellowship provided me with an opportunity to connect with an amazing group of brilliant and humble individuals, many of whom are leading researchers at Meta. Their readiness to help and share knowledge was inspiring, turning the learning experience into something truly priceless. In addition to standup meetings with my team, I often had insightful sessions with the researchers at Meta.
The MLH Fellowship fosters a culture of curiosity and passion for technology. The environment is vibrant and exciting, and I found it a true reflection of the world of tech.
Launch Your Career
My time in the MLH Fellowship has significantly bolstered my job search. I frequently discuss my experiences and skills gained during interviews, as they offer valuable insights into my capabilities. Of course, it’s also listed on my resume! If you are considering the MLH Fellowship, I encourage you to take the leap.