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Ross Carvalho ’25 built a successful career as a software engineer in India, but with the rise of , he knew it was time to take his skills to the next level and future-proof his career. “By 2022, I saw a trend,” Ross explains. “Companies weren’t just looking for software engineers; they wanted AI software engineers.”

Ross knew that to compete, he needed to build a greater basis of AI knowledge and began researching universities that offered strong programs with an AI-focus. He was drawn to graduate programs at Pace’s Seidenberg School of Computer Science and Information Systems, which integrates AI fundamentals throughout its curriculum. “At Pace, I’ve taken courses in deep learning, computer vision, and natural language processing,” he shares. “These are the fundamental blocks of AI, and Pace provides a solid foundation in these areas.”

Companies weren’t just looking for software engineers; they wanted AI software engineers.

As Ross prepared to begin his studies in New York City, he came across an opportunity that felt almost too perfect—a lab assistant position in Pace’s Computational Intelligence Lab. It was the ideal complement to the AI-focused curriculum he was pursuing—allowing him to not only learn, but actively contribute to AI projects.

He worked with fellow student, now adjunct professor Darsh Joshi ’24 who became a mentor to him, creating the infrastructure that would give students both the technology and the collaborative space to create AI models and predictive systems. They both envisioned the lab as a place to offer education ranging from data science concepts to practical industry experience. “We decided we wanted to bridge this gap from university to corporate by providing them these courses,” says Ross. “So, the lab performs those two functions right now. First is providing a platform that gives students access to computing services, and the second is providing educational content and mentoring sessions.”

It’s not just about learning in the classroom—it’s about applying those skills to solve real-world problems.

With his growing experience at Pace, Ross applied for internships during his first year, eventually landing a competitive six-week summer internship at Apple. Ross worked in one of Apple’s Bay Area campuses as a DevOps (development and operations) intern, helping manage the platform responsible for building applications like iMovie. “I worked on improving the platform, building a framework to test its various components, and even doing some production deployments, which was rare for interns,” said Ross.

Ross credits Pace’s Career Services with helping him secure the internship. “Career Services was incredibly helpful, especially with my resume. They taught me how to tailor my resume to specific job descriptions,” he says. “They provided personalized advice through multiple sessions, helping me tune my resume for each application.”

As Ross continues to build his expertise in AI, he remains grateful for the opportunities �����Ƶ has provided. “�����Ƶ has given me a platform to grow and explore,” he reflects. “It’s not just about learning in the classroom—it’s about applying those skills to solve real-world problems.”

Pace students have huge potential to create a big impact.

Since leaving India to continue his education, Ross has gone beyond basics with AI, finding mentorship and hands-on experiences to deepen his skills along the way. “�����Ƶ has given me a lot,” he says. “They have given me an on-campus job. They have provided me with guidance wherever required, especially from my mentors like Darsh Joshi, and all my friends here, my Pace family.”

For others looking to expand their AI expertise, Ross recommends students find problems where AI could have an impact and start there. ”Students should venture out. Focus, solve, participate in hackathons and competitions where these organizations work with us to actually solve a problem,” he says. “Pace students have huge potential to create a big impact.”

Learn more about AI and machine learning at Pace’s Computational Intelligence Lab.