Current Position and Industry

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Q: Can you describe your current position and what field/space you work in?

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A: Yeah, for sure. I am a machine learning engineer at a construction technology startup. What our company does is we put cameras on construction sites, and we create an app, a dashboard that a construction manager would have access to check out all their streams. And I'm working on the products, which are trying to identify people, cars, anything of interest for the construction manager in the interest of the safety and security of the site, as well as project management. So, we're kind of just like an intelligence solution that's built off of computer vision. Yeah, that's pretty much it.

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Typical Day at Work

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Q: What does a typical day look like for you?

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A: Yeah. Um, so we're a pretty small team. We're only about, I would say, 18 people. Our company is pretty international. We have the core of our engineering team in Croatia, but also some people in Brazil and Sri Lanka. So, I would say my day-to-day is when I get up, I'll come to our office, but I'm really picking up some of the work that's been given to me from our developers across the world. It's a lot of working on projects. I do a lot of R&D projects, updating people on the progress of the projects, trying new tools. In the world of computer vision, there's always new models being created, new strategies to explore. So, it's a lot of looking at academic research and trying to apply that to the problems I'm working on as well. Like there's a lot of operational stuff I need to lend my hand into because we're such a small team. So, some client success management as well.

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Career Interest

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Q: How did you first get interested in the work you're doing?

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A: Yeah, I'd say computer vision is kind of like a subset of data science. It's something that I didn't really learn about until after college. I took a data science immersive course after college, and we spent a little bit of time focusing on the world of computer vision. That's how I was introduced to it. I did a capstone project in it. Then I had a friend who created this company, and I learned about the company later on. I figured that my skill set and interests kind of aligned with it. So that's how I got interested in the topic and then got into my current position.

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Emerging Career Opportunities

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Q: What do you think are the most interesting career opportunities emerging for people who are going to be entering the job market in 5 to 10 years or so?

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A: Yeah, for sure. Well, as you guys are probably aware, artificial intelligence is being applied everywhere in the economy. It's really exploded in the last year with more generative AI tools like ChatGPT. Now you're seeing more image generative tools as well. From a prompt, you can generate images. I think there will be more AI solutions in different sectors of the economy like finance, manufacturing, construction, like what I'm working on now. Really, every business can have it in some way or another, including marketing. I mean, yeah, I'm kind of coming at it a little biased because I work in it, but I think it's something that's going to dominate the economy. People are going to use it in their jobs, and it's exploding. So, I would say that's an area that five to ten years from now, a lot of people will be working in or at least will be working with the tools. So, it's good to understand that.

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Advice for Young Enthusiasts

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Q: Do you have any specific advice for a young person interested in working in your field?

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A: Yeah, for sure. I think it's really important to have a strong foundation in physics, mathematics, computer science—like a really good fundamental understanding of that—because these are the concepts that are at the foundation of artificial intelligence. A lot of AI is just kind of experimenting, playing around with things that people at very impressive universities have created in their research. But I just think having a really good foundation in mathematics is important so you know what you're doing. Having an idea of how to design an experiment is really important. That's the primary thing. I never really got a chance to take AI courses in high school or college or anything like that. I'm sure it's really useful to dive into it when you're still in school, so I would take advantage of that. I know colleges now are offering more classes in that. I'd be pretty shocked if they didn't in high school. I don't think it's necessary in high school to really start taking career-oriented classes like that, but just working on your fundamentals—that's the number one thing.

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Short-term and Long-term Goals

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Q: Can you tell us a little about your short-term and long-term plans and goals?

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A: Yeah, for sure. I'd say in the short term, my goals are to improve our artificial intelligence product as much as possible. I'm working on improving our vehicle detection model and person detection model. I want to learn as much as I can about the most advanced techniques, the greatest models that are being used in the field, and then learn how I can apply it to our data and our problem. In the long term, I would really like to do something entrepreneurial and figure out if there's something that people think can be useful in the computer vision space, how I can fit into that, and how I can create something in that. So that's kind of how I'm thinking in the long term. But right now, I'm just focused on getting good experience and learning from smart people in this field because I'm still relatively new.

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Reflecting on the Career Path

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Q: Is there anything you would have done differently in your career path?

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A: Uh, yeah. I don't really regret not necessarily taking that. I think I would have poured a little bit more into the whole computer science side of this. I didn't really become adept in computer science until I started working. I think I could have benefited from focusing on that more in college. I wish I could have taken some classes in high school. Coding is another one of the big fundamentals that are important for this type of work. You're really interacting with artificial intelligence in code. That's probably where the regret is.