I’m Alisha Maddy, an aspiring Software Engineer pursuing a career in tech as a self-taught developer. After graduating with a bachelor’s degree in chemistry and biochemistry, I started teaching myself to code during the pandemic. While I love all things chemistry, it turns out I love coding even more, and I’ve been trying to get started in the industry since 2020. Major League Hacking (MLH) has empowered my career switch journey and played a pivotal role in shaping my path.
Discovering MLH
I first learned about MLH from a community college professor in early 2022 and immediately knew I needed to prepare myself for this opportunity. Until then, I had mostly taught myself by taking online courses and building personal projects, so I joined another learning community called CTI Accelerate in fall 2022 to build my teamwork skills. I was looking to break into open source and find another community to embark on this journey with, and that’s where the MLH Fellowship came in. I landed a spot with the MLH Prep program in April 2023 and realized how much fun it is to build cool projects with new friends. This experience helped me further hone my coding and teamwork skills and land a spot in the MLH Software Engineering Fellowship for the Fall 2023 term.
The Power of Pods
One of the best parts of the MLH experience is the sense of community fostered within pods. The pod — a team of Fellows and a Pod Leader — became the highlight of my fellowship journey.
I was in a pod with 12 Fellows from diverse corners of the world. We would meet three times a week under the guidance of our Pod Leader, Giancarlo, who was always supportive and inspiring. These meetings took the structure of a stand up or retrospective, a great learning experience since that’s how real software development teams operate.
In the pod, we were all assigned to different open source projects with Meta, allowing us to learn about each other’s contributions (and challenges) during our weekly discussions. Beyond these project-focused meetings, we would also play online team games and have 1:1s with others in the pod to get to know each other better and learn about each other’s goals.
The camaraderie within the pod was really inspiring and made me feel like I was actually attending university in-person again, even though the MLH Fellowship is a completely remote program. The MLH community does an incredible job of instilling a strong sense of belonging in the tech world, and the opportunity to collaborate with and learn from my podmates from different countries and continents broadened my perspective on global tech collaboration. As a non-traditional student, this was a transformative experience for me and made me feel connected and valued in an industry with a high barrier to entry.
Maintainer Collaboration
Over the 12 weeks of the MLH Fellowship, I contributed to the Fairseq2 project, which meant I got to work closely with real Meta Software Engineers that serve as maintainers for the project. Each week I’d meet with the maintainers to discuss the project, but the majority of communication took place asynchronously. This approach ensured that I not only had support when I encountered blockers but also had the space to independently tackle problems before seeking help.
As a Fellow, my main assignment was to integrate new libraries into Fairseq2, which required me to become an expert on these libraries. This assignment required a high level of self-sufficiency that pushed me to grow my technical and communication skills. I learned to own my project and effectively articulate localized issues without burdening mentors with unnecessary details, one of the most important skills I developed during the program. This is what truly made me feel like a Software Engineer and not just a student.
My Contributions
As a contributor to Fairseq2, my efforts focused on the fairseq2.data component, specifically enabling swift construction of data pipelines for machine learning tasks such as training, evaluation, and data preprocessing.
With the help of my mentors, I built an image decoder in C++ for building image data pipelines and a video decoder for video pipelines. Before my contributions, Fairseq2 only provided the ability to build text and audio data pipelines. The opportunity to make such an impact on a project at the forefront of tech innovation was extremely rewarding.
If you’re curious about my contributions, you can check out my contributions below!
What’s Next?
I’m thrilled to share that I’ll be participating in the MLH Fellowship again this spring as a Fellow with Seamless, another Meta project that enables translation and plain speech recognition! I’m excited to foster new connections within the MLH community and make further contributions to open source.
The support and camaraderie I experienced in my pod, and the guidance from mentors, have been instrumental in my growth. I’m grateful to the entire MLH community for serving as a cornerstone in my career transition from biochemistry to software engineering.