About the Team
Forecasting complex, fast-changing environments is one of AI’s hardest open problems. It spans multimodal learning, continual adaptation, synthetic data, and simulation. Financial markets are the ultimate testbed: massive open data, constant real-time feedback, and conditions that push ideas to their limits.
We’re building a research lab where top ML minds can explore their own directions while testing them against the toughest real-world system: markets. We’re a small, independent team with no bureaucracy, driven to rethink how complex systems are modeled and predicted — starting with markets and expanding to supply chains, energy, and beyond.
If you want your research to prove itself beyond theory, this is the place.
About the Role
As an AI researcher, you will join our research lab under supervision of Irina Rish's, Professor at the Université de Montréal (UdeM) and a core faculty member of MILA - Quebec AI Institute. You will own key parts of our core research agenda and shape the direction of our foundation models for markets. Depending on your expertise, you could focus on:
the design and training of a multimodal model — defining architectures, data strategies, and training objectives
scaling large models efficiently across multi-GPU setups, building distributed training pipelines
augmented data research — generating synthetic data pipelines (symbolic, numeric, and simulator-based) and integrating them into training
You’ll work at the frontier of real-world ML, with freedom to define problems, test ideas, and push them into live trading systems.
You might thrive in this role if you have
MS/PhD (or equivalent) in mathematics, computer science
2+ years experience in large foundational models research
Track record taking models prototype → scaled training → production inference
Strong publication record (NeurIPS, ICML, ICLR)
Experience in trading, hedge funds as a plus