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About the Role

We are seeking an experienced Senior Machine Learning Engineer to help shape, develop, and deliver AI applications and proof-of-concepts (POCs) across diverse business lines. The successful candidate will collaborate with stakeholders to identify opportunities, develop impactful solutions, and drive the adoption of advanced AI technologies across the organization. As a Senior Machine Learning Engineer, you will be a key member of a team, developing and deploying large-scale GenAI applications for enterprise use cases. You will build and optimize LLM-based solutions, RAG systems, agentic workflows, and production ML infrastructure that powers effective decision-making across RBC.

Responsibilities

Develop, and productionize advanced GenAI and AI solutions, ensuring they address complex business challenges with measurable impact and deliver tangible ROI
Optimize and deploy state-of-the-art ML models and AI agents, leveraging modern frameworks (e.g., LangChain, LangGraph, or similar) and best practices for scalability, reliability, and maintainability
Contribute to experimentation and continuous improvement cycles, including robust prompt engineering, model evaluation, A/B testing, and performance optimization of production GenAI systems
Build and maintain production-grade ML infrastructure including data pipelines, model serving endpoints, monitoring systems, and automated deployment workflows
Implement RAG (Retrieval-Augmented Generation) systems using vector databases, semantic search, and knowledge retrieval techniques to enhance LLM capabilities
Develop agentic AI workflows with multi-step reasoning, tool use, and orchestration to solve complex business problems autonomously
Collaborate with product managers, data engineers, and business stakeholders to translate requirements into technical specifications and working solutions
Write clean, maintainable, well-documented code following software engineering best practices including code reviews, testing, and version control
Stay current with emerging GenAI technologies and research, evaluating new models, frameworks, and techniques for potential adoption
Participate in technical design discussions and contribute to architectural decisions for GenAI applications and ML infrastructure
Ensure responsible AI practices including bias detection, model explainability, security, privacy, and compliance with enterprise governance standards
Document technical solutions, architectures, and processes to enable knowledge sharing and team scalability

Requirements

5+ years of experience in machine learning engineering with 2+ years focused on production ML systems
Hands-on experience building GenAI applications using LLMs, RAG, agents, or similar technologies in production environments
Strong proficiency in Python and modern ML frameworks (LangChain, LangGraph, Hugging Face, OpenAI API, Anthropic Claude, etc.)
Solid understanding of LLM architectures, prompt engineering, fine-tuning, and optimization techniques
Experience with cloud platforms (AWS/Azure/GCP) and containerization (Docker, Kubernetes)
Practical knowledge of MLOps practices including CI/CD, model monitoring, versioning, and deployment automation
Experience with vector databases (Pinecone, Weaviate, pgvector, Chroma) and semantic search systems
Strong problem-solving skills with ability to break down complex problems into implementable solutions
Excellent collaboration and communication skills with ability to work effectively in cross-functional teams
Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)
Experience in financial services or highly regulated industries with understanding of compliance and data privacy requirements
Knowledge of agentic AI architectures and multi-agent orchestration frameworks
Experience with real-time streaming data and event-driven architectures
Familiarity with distributed systems and high-scale data processing
Experience with A/B testing frameworks and experimentation platforms
Contributions to open-source ML/AI projects or technical blog posts
Experience with graph databases and knowledge graph construction
Understanding of transformer architectures and attention mechanisms

Skills

Big Data Management
Data Mining
Data Science
Deep Learning
Machine Learning (ML)
Predictive Analytics
Programming Languages

Location

RBC CENTRE, 155 WELLINGTON ST W:TORONTO
Toronto
Canada

Work Type

Full time

Experience Level

Senior

Education Level

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field (or equivalent practical experience)

Benefits

Competitive compensation and benefits package

About the Company

Global Functions Technologies impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformational IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.
At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.