From Curiosity to Career: Finding Purpose in Machine Learning
When Vansh Bhatia arrived for the MSc in Applied Computing (MScAC) program, he wasn’t following a rigid career plan; he was chasing a challenge.
“I knew I wanted to push myself,” he says. “I was interested in machine learning, and U of T felt like the right place for that, especially with its history in AI and the structure of the program.”
Before joining MScAC, Vansh completed his undergraduate degree at the SRM Institute of Science and Technology and gained hands-on experience working as an iOS developer and later as a full-stack developer. But he was ready for something bigger; something deeper.
That’s where MScAC came in.
Finding Direction Through Experience
Interestingly, Vansh didn’t enter the program with a fixed career path. It was through the coursework and hands-on exposure to machine learning that things started to click.
“Once I got into the program, I realized how much I enjoyed ML research and development. That’s when I knew this is what I wanted to do.”
Today, after graduating, he’s doing exactly that: working in machine learning at AMD as a Software Development Engineer II, continuing the same line of work he started during his internship.
“The Networking is on Another Level”
Ask Vansh about the biggest highlight of MScAC, and his answer is immediate: the people.
“The networking here is on another level,” he says. “The program really invests in making sure students connect with peers, alumni and industry.”
Those connections weren’t just nice to have; they were transformative. Before even starting his internship, Vansh had already gained insight into what to expect, thanks to conversations with senior students.
“I knew what the interview process looked like, what the role would involve. Just by talking to people ahead of me. And now I’m doing the same, helping students coming in.”
That cycle of mentorship is something he sees as a defining strength of the program.
Turning Opportunity into Impact
Vansh interned at AMD in Markham, Greater Toronto Area (GTA), where he worked on cutting-edge research in multimodal AI: technology that allows systems to reason across different types of data, like text and images.
“I was drawn to the real-world impact of the project,” he explains. “It wasn’t just theoretical; it had direct applications in how models perform and how companies make decisions.”
His work focused on making large language models more efficient, helping them reach the same conclusions while using fewer computational resources. The project contributed to ongoing research, including a benchmarking paper and dataset development.
And it paid off. After his internship, Vansh secured a full-time role on the same team.
Why Toronto (and MScAC) Stand Out
For Vansh, being in the GTA was another major advantage.
“There are so many tech companies here looking for the exact skills we’re building,” he says. “Between the program’s networking events and the broader tech ecosystem, there are a lot of opportunities.”
He emphasizes that while opportunities are abundant, preparation is key.
“A lot of my interview questions were directly based on what we learned in class. The curriculum is very current and relevant, so taking your courses seriously really matters.”
Advice for Future Students
If there’s one thing Vansh would tell incoming students, it’s this: start early and connect often.
“Prepare from day one. And talk to people: your classmates, seniors and alumni. Especially if you’re new to Canada, networking makes a huge difference.”
