UNLV students highlight the difference between their summer internship reality and what we see on the big screen.
Author: Lola Lopez
If you’ve ever tuned into a film or TV program, chances are you’ve seen an office intern relegated to menial tasks, like endless coffee runs. If that’s all there is to internships, why do them at all?
Over the summer, students combined their classroom knowledge with real-world experience to meet corporate vice presidents, design AI models, manage teams, and more. To differentiate real life from the big screen, we’ve paired up UNLV interns with film and TV counterparts.
Movie Version: Waitress Dreux Jones hopes to make it to her interview and become a franchise manager to an iconic L.A. restaurant in One of Them Days.
The UNLV Intern Version: Hospitality major Joseph Snyder manages a staff of 12 to 15 people for events of up to 400 guests as a banquet leadership intern for the The Union League of Philadelphia. He’s gained experience in managing weddings, mitzvahs, graduation celebrations, corporate meetings, and golf outings.
His biggest takeaway? The power of taking the extra step to provide great service.
“The most memorable moments of this internship have been when I have been able to connect with the club’s membership. The unique nature of private clubs compared to other facets of hospitality is the fact that you are serving the same people day after day, meaning that you are able to connect and create deep meaningful relationships with the people you serve day after day.”
Show Version: In an episode of the anthology series Black Mirror, characters Frank and Amy meet on a dating app that uses a simulation to determine their compatibility.
The UNLV Intern Version: Computer science major Melissa Swinehart’s main responsibility at the AI-EDGE Institute at the National Science Foundation was designing a generative AI model and training it with her own dataset. Starting with the basics, she learned about different machine learning models and how to train them, which came with mastering the math behind them.
“This internship boosted my confidence personally, academically, and professionally. Being confident in your work and clearly explaining it to others isn’t always easy. This internship provided all the tools I needed, but the best part was creating something myself,” Swinehart said.
“Once I started experimenting, I got to understand better how my mind works, what ideas I could come up with, how I could build on them, and how I could clearly explain it to other people. I absolutely loved my internship. It was my first real exposure to machine learning, and honestly, I fell in love. I enjoyed having the freedom to be creative, designing different models, and applying them to various use cases.”
