Senior Machine Learning Engineer

RBC•Toronto, ON

4d•Onsite

About The Position

Join CMTC at an inflection point where commercial banking meets the frontier of artificial intelligence. As a Machine Learning Engineer on our team, you will be at the center of RBC's strategic push to embed AI and Data into core commercial banking workflows, building models and platforms that directly shape how commercial clients experience banking. This is not a research role, so you will own end-to-end delivery of production ML systems that drive real business outcomes across risk, client intelligence, and automation. You will collaborate with data scientists, engineers, and business leaders across the organization, with access to rich, complex datasets and meaningful problems at scale. If you want to build AI that matters and just prototypes, but deployed, impactful solutions, this is the role for you.

Requirements

Hands-on experience building and deploying ML models in a production environment
Proficiency in Python and core ML libraries (scikit-learn, PyTorch, TensorFlow, or equivalent)
Experience with MLOps practices — feature stores, model registries, CI/CD for ML, cloud deployments, monitoring and drift detection
Strong understanding of supervised/unsupervised learning, model evaluation, and statistical fundamentals
Ability to communicate complex model outputs clearly to non-technical business stakeholders
Experience working with large, structured datasets and cloud platforms (OCP, AWS, etc)

Nice To Haves

Experience in financial services, banking, or regulated industries
Familiarity with NLP, LLMs, or generative AI applications in an enterprise context including active production deployment
Knowledge of responsible AI principles; explainability, bias detection, model governance
Experience in a large, matrixed organization with multiple competing priorities

Responsibilities

Design, build, and deploy production-grade machine learning models that power AI use cases across commercial banking (transaction intelligence, client intelligence, automation, anomaly detection)
Collaborate with data scientists and data engineers to translate experimental models into scalable, maintainable ML pipelines and services
Partner with business stakeholders to understand commercial banking problems and frame them as solvable ML problems
Develop and maintain MLOps infrastructure on-prem including model training, versioning, monitoring, and retraining pipelines
Ensure model reliability, fairness, and compliance with RBC's risk and governance standards
Work cross-functionally with engineering, product, and compliance teams to integrate ML solutions into existing banking platforms
Continuously evaluate emerging AI/ML tools and frameworks to improve team velocity and solution quality
Be a power user of latest LLM models for your day-to-day work load and contribute to CMTC's AI roadmap by identifying new opportunities where ML can create measurable business value

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