AI Model Risk Validator & Research Scientist

RBC; Toronto; On-site; CAD 110,000 - 170,000; Full time

Job summary

RBC, a global financial leader, seeks an AI validation professional in Toronto to assess and manage model risk arising from AI initiatives. The role focuses on validating LLM-based apps and agentic AI systems within Enterprise Model Risk Management.

You will explore conventional ML methods, collaborate across functions, and contribute to reusable software packages while applying state-of-the-art research to real-world problems.

Qualifications

• Pursuit of a PhD or Master’s degree in a quantitative field such as statistics, CS, applied mathematics, econometrics, engineering, or quantitative finance.
• Proficient Python; able to write and run research experiments and clean code.
• Familiar with popular LLMs and agentic frameworks.
• Strong communication and interpersonal skills.

Responsibilities

• Validate LLM-based applications and agentic AI systems, and assess associated risks.
• Validate traditional ML models (classification, regression, NLP, RL, recommender systems).
• Challenge models conceptually and empirically, focusing on soundness, reproducibility, fairness, privacy, and explainability.

Skills

Python

Statistics

LLMs

Research

Communication

Education

Masters/PhD in related quantitative field

Tools

Git

Linux

ML Frameworks

Job description

RBC, a global financial leader, seeks an AI validation professional in Toronto to assess and manage model risk arising from AI initiatives. The role focuses on validating LLM-based apps and agentic AI systems within Enterprise Model Risk Management.

You will explore conventional ML methods, collaborate across functions, and contribute to reusable software packages while applying state-of-the-art research to real-world problems.