Research Team

Research sits at the core of everyone’s work at Borealis. Cutting-edge research requires diversity of perspectives, tenacity, and creative thinking to fundamentally advance what is possible in Machine Learning. Join our team of approximately 40 researchers with backgrounds across artificial intelligence including computer vision, machine learning, and natural language processing, with PhDs in computer science, physics, computational finance, mathematics and more. 

We work with large-scale datasets, derive impactful machine learning models and collaborate with machine learning product owners and software engineers to help bring research and prototypes to life – and reimagine the future of financial services. Together, we published over 50 papers in NeurIPS, ICLR, ICML, ACL, CVPR and other conferences and journals. We also do focused work in areas of AI that stand to generate value across the financial sector and beyond.

Join the team

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  • “Very rarely do you get to see so many talented people from different research domains working together, whatever question you have, you can always find an in-house expert!”

    Wenjie Zi

    Senior Research Engineer

  • “What brought me to Borealis in 2017 and keeps here today is the diversity of our team on all fronts; cultural, academic, and beyond, we never stop learning from each other.”

    Christopher Srinivasa

    Senior Research Team Lead

  • “We work towards state-of-the-art solutions for challenging financial problems. This is an opportunity to be the first who invents an AI for financial services with huge business impact.”

    Hossein Hajimirsadeghi

    Principal Researcher

  • “My favourite thing about RBC Borealis is that I am working with amazing people who are highly talented, smart and inspiring.”

    Nazanin Mehrasa

    Machine Learning Researcher

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We’re hiring! 👋

ML Research Internships

Research interns work with all our teams, collaborate with RBC on large-scale projects, and publish original research.

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Responsible AI

AI permeates our daily lives, and ensuring it is being developed and used in a responsible and ethical way has become a top priority. We’ve created RESPECT AI platform to share research, tooling, tutorials, code, and know-how to contribute to the safe AI community and accelerate responsible AI adoption.

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North Star Research

We focus on a set of challenging North Star research problems: Asynchronous Temporal Models, Non-Cooperative Learning in Competing Markets, and Causal Machine Learning from Observational Data.

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