What it's like to work in AI at Capital One

Melissa often begins her day prepping for a call with an academic partner, tapping into Capital One's network of top research institutions to discuss the latest AI safety and research publications. As a manager, her role centers on responsible innovation, ensuring that theoretical AI is always applied with care. 

Her unique path to AI began in climate modeling, where her PhD work on atmospheric simulations built a foundation in complex systems that still shapes her approach. "We’re not doing research in a vacuum," she said. "We’re responsible for making sure our ideas lead to tools that are safe, fair and useful."

Tyler’s days are spent bringing those theories to life. He starts his day by reviewing the latest research shared by his team, then identifying which methods can be operationalized into tangible systems. "I try to carve out at least two deep work sessions a day," he said, where he focuses on implementing and executing experiments, then analyzing results before syncing with teammates on an experiment or code review.

This hands-on experimentation, coupled with Capital One's long-term investments in infrastructure, data, advanced tooling and AI training, gives associates like Tyler and Melissa the robust platform and leadership support they need to move fast and think big.

Abhijit Bose, Capital One SVP and Head of Enterprise AI/ML platform technology, believes that success in AI hinges on having engineers who blend creative problem-solving with deep expertise in both AI fundamentals and large-scale distributed systems. They also need to stay current with the latest research.

“These specialized skillsets have become some of the most critical drivers of our transformation,” Abhijit said. “Our AI engineers are reimagining systems and shaping how AI shows up across the company.”

Autonomy with purpose

Both Melissa and Tyler feel a deep sense of engagement in their work, thanks to the strong team culture at Capital One that supports new ideas and celebrates curiosity. They’ve found the rare space where deep research and real-world relevance overlap.

“There’s a lot of trust,” Tyler said. “If you have an idea, there’s space to run with it and support to bring it to life.”

Melissa agrees. “There’s no rigid playbook,” she said. "I can choose based on my interest and my expertise where I shift my focus. I'm in full ownership of that in terms of how I conduct AI research and what kind of research I choose to do."

This kind of environment helps associates move quickly, think creatively and keep learning, which are essential in a field that’s changing every day like AI. Melissa regularly publishes findings and presents her work at industry conferences—she recently spoke at the International Conference on Machine Learning, and her team’s work on AI safety earned top-paper honors. Tyler regularly attends AI conferences and helps onboard new PhDs to the team.

Looking ahead

From mentoring PhD interns to contributing to academic research, associates like Melissa and Tyler are doing work that challenges them and shapes the future of AI. 

"We’re creating tools and ideas that will influence how AI gets used for years to come," Tyler said. "It’s exciting and fulfilling."

Ready to grow your tech career like Melissa and Tyler? Explore AI jobs at Capital One.