Earlier this year, I joined integrate.ai as a platform software engineer through The University of Waterloo’s co-op program. At that point, I was no stranger to Toronto’s vibrant tech scene. I’d already gained experience in mobile gaming and in the digital advertising ecosystem. That said, I’d never worked at an AI startup.
I was definitely a bit nervous. But, like they say, magic happens when you step outside of your comfort zone. That’s why I’d like to pay it forward and share some of that magic. So, here are three big lessons I learned during my time at integrate.ai.
1) Embrace ambiguity
Machine learning is still relatively new. Using it within a business context to drive decision making is even newer. As a result, no one has figured out the “best way” to do it—yet. Because there aren’t any set rules, the space can be ambiguous, and ambiguity can be… well, uncomfortable.
Ambiguity also represents an unprecedented opportunity for personal growth. At Integrate, you aren’t just learning how to do everything from scratch, you’re also setting the standard for how things should be done. Being at the cutting edge can be scary, but it’s also exciting.
When I was designing the data shape for our machine learning platform, I couldn’t rely on a set methodology. I had to do my own research. I was building a tool for machine learning experts, so I had to understand their pain points and use case. Cross-functional collaboration is necessary if you want to build a full and complete product. Even though there wasn’t a “template” for me to follow, it was a lot of fun just figuring things out, like I was a user experience detective.
2) Take action
By stepping outside of my comfort zone and seeking out the opportunities I wanted, I was able to work on things I otherwise wouldn’t have.
Early on in my internship, I booked a meeting with one of the machine learning scientists to talk about potential projects I could help out with. I was incredibly nervous. I didn’t know much about machine learning. What did I have to bring to the table? Was I wasting this person’s time?
Thankfully, I didn’t let these thoughts discourage me. Because I showed interest, I was invited to participate in Integrate’s onsite machine learning classes, where I attended lectures on reinforcement learning and completed weekly assignments. By the end of the program, I constructed a model and conducted experiments using the concepts I learned in a real-world use case.
After finishing my initial internship project, I was able to implement some Tensorflow algorithms for our platform. This was entirely new to me, and people didn’t expect me to have all the answers, so it was important to ask for clarification and guidance. Ultimately, by showing a bit of initiative and letting my curiosity guide me, I picked up some invaluable skills and got the opportunity to meet new people.
3) Ask for feedback and listen
integrate.ai has built a culture of feedback. In my first week, the COO gave new hires a challenge—to give and receive a piece of feedback by the end of the following week. Meetings always started and ended by asking for feedback. Everyone was helpful, and it was a great opportunity to learn from the best in the industry. Ultimately, Integrate’s feedback culture taught me how to become a better collaborator. It challenged me to question assumptions about my own work and empowered me to consistently raise the bar. On the flip side, I learned how to give valuable feedback and saw how impactful it could be on my colleagues’ work.
My internship at Integrate didn’t just give me a chance to learn from some of the sharpest minds in Toronto’s AI scene. It also gave me practical, hands-on experience. I got the opportunity to play a central role helping team members build a product from the ground up. More than that, I got to meet people who were as kind as they were intelligent. I can’t wait to see what the future has in store for Integrate!