My Experience as a Gympass Machine Learning Intern
From my past experiences, I know how hard it is to find an intern position as a Machine Learning (ML) Engineer, especially in Manaus, the city I currently live in. I wasn’t necessarily looking for one at the moment but then…Gympass came into play!
I am part of the student organization at my university, the Federal University of Amazonas (UFAM). Gympass approached us as it wanted to get closer to our university. We had a meeting to get to know more about Gympass and to discuss possible partnerships. As a member of the organization, I had to present myself and talk about my past experiences and very fortunately they were indeed looking for a ML intern! Their recruiter reached out to me later on, I took part in the interview process and luckily was a fit for the role. My process involved a couple of interviews with the team. One of them was conducted in English, as the head of the area is based in our NYC office.
Since my first day I have had so many great experiences that I have decided to separate them into two main sections:
- Cultural
- Technical
Cultural
During the onboarding process, the new employees and interns were introduced to the company’s 12 values. At that moment I realized that the cultural aspects were aligned with mine and that made me so happy!
Some of our values are:
- Having a talented team working together to achieve amazing results
- Having an ownership mentality
- Creating a positive and diverse environment
Not hard to understand how much my values aligned with those, right?
What is it like to be a Gympasser?
Being a Gympasser means seeking knowledge and learning together, as a team. The common advice I got was to take it easy and remember that I’m an intern, my team knows that I’m here to learn and they expect nothing but that. My teammates are always available to teach me so it makes me comfortable asking for help.
But what about meeting people outside my team? Well, I joined some affinity groups which made me interact with people from different areas. In the groups, we work together towards a common interest which in my case were black people and women.
And last but not least, besides working at Gympass I also use its app! I live the mission by seeking an active lifestyle.
Technical
What are the roles and responsibilities?
Before actually getting into my challenges in the area let’s talk about the main roles: ML engineer and data scientist. Let’s learn about the differences between them in a simple way.
ML Engineer
Focus on deploying pipelines and large-scale machine learning products.
Data Scientist
Focus on developing, training, and optimizing models, wrangling, exploring, and analyzing data.
In my hiring process, I was asked which path I wanted to take, and I chose ML engineering because I was interested in learning how to scale-out a theoretical model into a production-level model.
What have I done so far?
I’ve been in the company for only 3 months (although it feels like a whole semester). My first month was mainly dedicated to learning about the company’s structure. In the onboarding process, I had meetings with many managers from different departments to get to know about their area and structure, and by the end of the process, I learned about the entire Gympass stack.
If you are interested in learning more about our stack, check this out.
After that, I started getting small tasks from my mentor that entailed learning and presenting new technology or frameworks to the team that could be helpful for their workflow. This is a way of slowly understanding my team’s process of development since I need to see how the suggested technology is going to impact our development.
My everyday routine is like this:
- Talking with my mentor and presenting the progress of my current task or setting a new task.
- Participating in a few meetings to keep up with the team and the company’s progress and goals.
- To eventually ask for help in my current task.
What are my challenges in the area?
I guess the main challenge is having so many stacks to learn. In my first 1:1 meeting with my mentor, I was introduced to the stacks used in our team, and being honest, I was a little scared. Most of the technologies I already knew about, but have never worked with. Thankfully my mentor guided me, showing where to start and what I would need to learn to have a good foundation.
I’m still learning every day, I would not say that I’m close to being a full ML engineer but as an intern, I’m not expected to know everything, my main goal is to learn as much as possible.
And if you are interested in becoming an ML intern, here are some tips for you:
- Understand how an ML project is structured.
- Learn about the ML stack used in your company.
- Understand the difference between supervised and unsupervised learning.
- Attend workshops and lectures on ML and Big Data.
- Keep up with the news in the ML world.
- Don’t be afraid to ask questions.
- Don’t be afraid to fail.
In conclusion, this internship is being one of the best learning experiences that I’ve had so far and I look forward to being part of the company, turning my internship into a job.
