Inside Ople – Sam Gluss
Every start-up faces growing pains, but, a successful company brings each member’s experience together to overcome the challenges. That’s why the willingness to learn is a significant characteristic of people at Ople. We want everyone to be comfortable learning new things, and Sam Gluss is a true learner, bringing a wide range of experience to the team.
Tell us a little bit about yourself.
I love getting my hands on things. I love learning how to do different things. Maybe, I love learning too much because it took forever for me to get my degree in Computer Science. When I was earning my baccalaureate, I had many jobs, a bit too many. I worked at a pizza shop, I worked as a car mechanic for a while, I worked in alternative energy, I worked in electronics manufacturing, and I worked at a start-up making robotics coffee machines when I received an acceptance letter from San Francisco State to enroll in their Computer Science program. I finally sold myself on being a full-time student, and, I loved it. I was fortunate to study under great professors such as Kaz Okada and Jozo Dujmovic, who not only opened doors to artificial intelligence and project planning but also shared great real-life examples that taught me how I could become a great software engineer.
What happened after college?
So after college, I started to work in the software industry, but I always marketed myself as a generalist who can bring strong values to the company. I worked at both small and large companies. I worked as a front-end, back-end, and machine learning engineer before joining Ople. Given that I am doing all the three engineering jobs and more right now, I am definitely a generalist.
Tell me more about your experience at the previous companies.
The large company experience was very different. If I could update a progress bar on one of our apps in a quarter, it was a victory. Most things were compartmentalized and slow. The small company was more similar to Ople, of course. I was able to shift around and take on different projects. In fact, that’s how I got into machine learning. One of my colleagues there was a very seasoned software engineer, and, he needed to build a machine learning model for the back-end. Since it was not his expertise, he had challenges, so, I jumped in and asked if I can give it a shot.
Having no background in machine learning, it was a challenge for me. But, I had some experience in the statistical analysis, so it didn’t take long for me to grasp the job. I was able to produce a model that gave better predictions than what AWS provided as an ML solution. In doing so, I began to learn about the challenges of AI and Data Science. By the time I applied to Ople, I understood the value that Ople’s AI software and how it could accelerate the Data Science process at my former companies. Of course, I still have lots to learn at Ople from Giba and Petr to become better at machine learning, but I am excited about what we are creating.
What was the most interesting aspect of machine learning as you studied more?
I want to say “pattern recognition.” I am an engineer, so I have been trained to think in binaries. Something is either on or off, and based on that, the next thing happens. Machine learning is different because it’s not just on or off. The computer is able to poke around and check different patterns, both linear and nonlinear, to find patterns that we humans cannot see. That’s just fascinating to me.
Are you enjoying your job?
Oh yes, very much. As I mentioned, the decision to join Ople was triggered by the fact that I had just delivered a very long and tedious task that Ople could have delivered in minutes. At Ople, the coding challenge I received and the onsite interview questions were tangible to me because they were related to my most recent project. While I was sitting in the conference room chatting with everyone at Ople, I was thinking ‘my gosh, I would have saved five months of my time if I had used Ople.’ Then I imagined how the world would change if everyone had Ople as their AI tool. I understand that there are science and fun behind the fine-tuning of models, but, that’s not the core value you get out of producing models. Think of hash tables. You can definitely spend time setting all the coefficients and resize the tables and whatnot, but most people just create one and use it. With Ople, people will be able to simply produce machine learning models and quickly use them, not worrying about feature engineering and hyperparameter tuning. Going back to your question, I enjoy my job because I am creating the future with a team of wonderful colleagues. I actually enjoy going to work.
What do you like to do for fun?
I race with the American Federation of Motorcyclists. It’s my go-to-hands on activity. When I am away from my desk, I race and fix my bike. Just recently, I had to learn to weld because I had to replace all the plastics on my bike with Kevlar.
The other thing I really enjoy is the Flight Simulator. I have the whole flight simulator rig at home, which I don’t have much time for, but, one of my bucket list items for 2019 is to fly a real plane. You don’t have to be a Wright brother anymore, right?
What is your favorite quote?
My favorite quote is from Neil Armstrong - “It suddenly struck me that that tiny pea, pretty and blue, was the Earth. I put up my thumb and shut one eye, and my thumb blotted out the planet Earth. I didn't feel like a giant. I felt very, very small.”
My interpretation of the quote is why be satisfied with the status quo when there is so much more to explore? It’s what we always say at our meetings, “be proud but never satisfied.” Keep moving, innovating, and enjoy everything to it’s fullest.