Lead, Machine Learning Engineer, GFT

RBC•Toronto, ON

4d•Onsite

About The Position

As a Senior Manager, AI and ML, you will be working on solving core business problems in compliance (trade surveillance, managing regulatory insights, etc) by leveraging AI and ML to optimize business processes and facilitate informed decision making. You will get the opportunity to work on cutting-edge technology and complex problems that generate significant value and have a high long-term impact on the bank’s growth.

Requirements

PhD or Masters in a quantitative discipline such as computer science, mathematics, statistics, or engineering
Excellent verbal and written communication skills; ability to work collaboratively with cross-functional teams including business, engineering, and risk management
7+ years of expert level programming experience in Python (preferable) and other languages is a must – ability to write production level code and documentation
5+ years’ experience working with large unstructured and structured datasets - exploring and understanding data, cleaning and pre-processing, performing exploratory data analysis, generating business insights and communicating them in a clear, concise manner
5+ years’ experience developing and deploying models in production for real business problems
Knowledge of standard machine learning libraries like numpy, pandas, scikit learn and visualization packages like seaborn or matplotllib, etc and machine learning algorithms like logistic regression, tree based models, decision trees, random forests, etc
Strong understanding and work experience with core NLP and Generative AI like embeddings, text pre-processing, RNN’s, Transformer architecture, fine-tuning models, prompting techniques, etc
Demonstrated experience designing and implementing Retrieval-Augmented Generation (RAG) architectures, including vector databases, embedding models, and retrieval pipelines
Experience building and deploying RESTful APIs for ML model serving (FastAPI, Flask)
Experience with MLOps practices, model serving, monitoring, and CI/CD pipelines for ML systems
Experience working with version control – git and linux.

Nice To Haves

Experience building autonomous AI agents and multi-agent orchestration frameworks (e.g., LangChain, LangGraph, AutoGen)
Prior experience in financial services, particularly in Compliance, Risk, or Regulatory Technology
Experience working with big data, pyspark, scala
Experience working with deep learning – RNN’s, Transformer models, etc
2+ years’ experience working with Deep Learning Frameworks like Tensorflow or Pytorch

Responsibilities

Work on challenging business problems by leveraging large RBC data, translating them into machine learning problems and applying advanced machine learning algorithms to generate business value
Lead the end-to-end lifecycle of AI/ML initiatives—from ideation and POC through development, deployment, and production support
Design and implement Generative AI solutions, including Retrieval-Augmented Generation (RAG) systems, LLM-powered agents, and NLP pipelines
Provide technical leadership and mentorship to team members, fostering a culture of innovation and continuous learning
Collaborate with engineering, architecture, and model risk management teams to ensure solutions meet enterprise standards for scalability, security, and governance
Stay current with emerging AI/ML technologies and evaluate their applicability to Compliance use cases
Communicate complex technical concepts to non-technical stakeholders and senior leadership

Benefits

bonuses
flexible benefits
competitive compensation
commissions
stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Opportunities to do challenging work
Opportunities to take on progressively greater accountabilities
Opportunities to build close relationships with clients
Access to a variety of job opportunities across business and geographies