How I Went From Acting to Data Labeling and Machine Learning
As much as Data labeling and Machine Learning could be considered the ‘new things in tech’, those are not careers you would normally hear kids saying they would like to pursue. As one of the many professional paths that didn’t exist a while ago, these areas are still unknown to many young adults and are not part of the school curriculum in many countries, but they have become essential for the development of Artificial Intelligence and its sub-areas.
Growing Up With Big Dreams
If when I was a child in my native Brazil you had asked me what I wanted to do as an adult, you would have heard something enthusiastic along the lines of ‘I want to be an actor’! And in a country where many don’t get the same opportunities, I was lucky enough to have had a chance to study dramatic arts for a long time, and I even worked in the film industry for a while upon graduating. Nowadays, I find myself as part of Brainly’s efforts to enhance the company’s Artificial Intelligence mechanisms, acting as a Data Labeling Lead. As far apart as those two professions may seem, both require trying to understand and mimic human decision-making. So let me tell you a bit about my journey and how I came to love what I do after transitioning from this unusual starting point.
I was born in Santos, Brazil, and started studying theater at 10 years old. Having always had a creative mindset, I also grew up exploring tap dance, ballet, jazz, and other types of modern cultural expressions. And despite being a good student, I always struggled with STEM subjects. I could not imagine using those teachings in ‘real life’. In fact, they seemed like something I had to learn, but that would have no practical use in my day-to-day.
After I finished High School, I went to Los Angeles to study English. I felt it was a chance for me to fulfill my dreams and start diving into the filmmaking and acting world. And for a period of time, I did manage to live the so-called ‘Hollywood dream’. I was auditioning for different acting roles every week; I was acting in music videos for bands I looked up to, and I also appeared on billboards and advertising campaigns for renowned international brands. So once I completed my studies 4 years later, I did not want to go back to Brazil. Instead, I decided to move to Spain and try my luck in the European film industry.
That’s when things started to get tricky: not being a native speaker of Spanish, I had a hard time auditioning for roles that required a perfect accent. So I started waiting tables in order to pay my bills, and a few months later, I landed a job as a Customer Service Agent for a large tech company, working with the Brazilian and Portuguese markets. I soon realized that the new opportunity had opened a wide range of fresh possibilities for me.
Entering the Tech Industry
Very quickly, I realized that all of the acting and improvisation classes I had taken in Los Angeles would be very useful as a Customer Service Agent. Due to having learned a lot about different communication skills, I was great at assisting customers over the phone, which caught the attention of my supervisors. It turns out that, much to my own surprise, I was also really good at understanding and suggesting improvements for technical processes and for the quality assurance team.
Within 4 months, I was promoted to subject matter expert and then to Team Leader. As a leader and supervisor, I felt great and more fulfilled than ever. I started to see how important the big operational parts of the projects were and to understand more about all the complexity needed to deliver high-quality results and enhance customer satisfaction.
From that point on, I knew that I wanted to focus my efforts on being a positive leader for the team, especially in an area that demanded a lot of empathy as well as organizational and analytical skills. Over time, the desire to work for a company advancing a product I believed in became essential to my career choices.
That’s when I first heard about Brainly. I realized that working in the education sector could offer me the opportunity to put my skills to the best possible use. Once a role became available in the Content Demand team, I applied immediately; when the job offer became a reality, I was genuinely thrilled. While working for Brainly’s Content team, I had the chance to get to know the company and its products as well as get acquainted with the teams and colleagues that helped build them. It’s truly amazing how much insight Brainly has to offer about education and how much effort we put into understanding how it works in different countries. I worked hard to absorb everything I could while being in charge of daily tasks related to content and to testing improvements for them.
The Content Demand team at Brainly ensures that students will come to our platform when they are looking for homework help and learning new topics. The team’s ultimate goal is to enrich Brainly’s knowledge base by adding questions that are in popular demand based on predictions or research. I can honestly say working on these tasks was great fun. It was a perfect chance to exercise both my analytical and creative sides to help improve processes that were already in place as well as explore new content sources. In order to automate some of those processes, I started to study Python, something that Brainly supported by allowing me, as it allows all of its employees, to enhance my skills through an annual 800 USD individual professional development budget.
Internal Mobility: the Perfect Enabler
During my time as a Content Demand Specialist, Brainly got massively involved in Machine Learning. The company’s aim is to help students find the answers that most accurately meet their needs in our extensive database, which includes millions of educational pages. After working for one year as a content specialist, I was approached by a Brainly colleague who was moving from the Content team to Machine Learning. She told me that her new manager was looking for someone to work on Data Labeling, and due to our previous collaboration in the content area, she felt that data labeling required a similar skillset to the one I had. They needed someone who was good at working with big amounts of data in order to organize and look for patterns.
Even though she had motivated me to apply for the role, I was a bit unsure at first. I didn’t know much about Machine Learning or Data Labeling and I had attended some of the machine learning monthly meetings and felt I didn’t entirely understand what they were talking about.
But the truth is that I remained intrigued by the topic, so I started researching. I found out that data labeling is basically classifying or tagging data (images, text, photos, videos, audios, and so on) into categories, which then serve as ‘examples’ used to train a machine learning model. In theory, what sounded complicated at first could be as simple as labeling 1,000 mixed photos of cats and dogs within two labels/categories: ‘cats’ and ‘dogs’. Usually, the more examples humans offer through data labeling, the better the machine-learning model can perform.
I’ve also learned about how machine learning, deep learning, and NLP (natural language processing) are essentially techniques to perform Artificial Intelligence.
After a few days of digging into the AI world, I decided I wanted to apply for the job. Dealing with ML projects seemed to have a lot in common with project management. Also, the whole AI industry will be highly present in our lives going forward, so this felt like a great opportunity to dive into a new, prosperous career. Ultimately, the fact that my work would be serving students using Brainly to learn made me proud and further motivated me to take on the challenge.
During the whole application process, I studied a lot, and in those weeks, I was fully committed to showing the AI team how much I wanted the role and how my creative mindset could add to the tasks and challenges at hand.
Learning, My Way
After so much effort, it was immensely rewarding to hear that I had been chosen to be one of the three first Data Labeling leads at Brainly. Data labeling is a pillar of our AI strategy in improving the learning paths of students across the globe. We want to identify and understand their learning obstacles to be able to provide them with the content they need by helping them access the Brainly products that meet their needs more closely.
We execute a data-centric AI paradigm both for R&D and production automations like continuous learning, as well as for continuous testing. On a daily basis, I work with data scientists, ML engineers, data architects, data analysts, and delivery managers, to name a few. It is incredibly inspiring to have so many talented people around, hear new perspectives about new and upcoming technology, and also offer my own thoughts and ideas. Our team is always exchanging: we discuss our ideas, challenges and achievements openly, and that in itself is a great experience.
Besides offering me the opportunity to transition into a data labeling role after only one year as a Content Demand Specialist, Brainly has also provided me with the chance to exercise another passion of mine: advocating for gender-affirming policies. Currently, I am leading the PRISM initiative, Brainly’s LGBTQIA+ Employee Resource Group. And I am also involved in organizing some of Brainly Cares’ initiatives, which are aimed at offering financial and other support for educational non-profits that the employees and the company believe in.
It was through my work on Brainly Cares that I had the opportunity to teach Brazilian teenagers from Projecto Uerê, a school at Rio de Janeiro’s “Favela da Maré”, about Artificial Intelligence. We discussed possible career paths for them and answered their questions about ML and AI. The students were very engaged, as the topic had been a suggestion of theirs.
Through all of the changes and the work, I can confidently say that I continue to learn more and more each day. I’m now completing a few courses in Python programming, which I believe will help me analyze big amounts of labeled data and automate some processes in the future. I’m also getting a SCRUM/PSPO certification. I don’t know what the next steps in my career will be, but after transitioning from Actor to Customer Support Agent and Team Leader, and from there into a Content Demand and Data Labeling Specialist, I do know that the possibilities are endless. And I’m beyond happy to know that, by working at Brainly, a company that supports their employee’s learning paths, I will be given both the tools to learn the skills I need as well as the opportunities to put them into action.
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The article came together thanks to a collaboration with Gabriele Jimenez.
