Job DescriptionWhat is the opportunity?This is an opportunity to work at RBC Wealth Management Technology Data team with a group of technology professionals dedicated to delivering transformative ML solutions to Wealth business and clients. We are all in with Agile development, DevOps, Open Source, Software as a Service (SaaS) and modern tools and processes.
We are looking for an experienced and visionary Staff Machine Learning Engineer to spearhead advanced ML initiatives, lead end-to-end project delivery, manage and mentor a high-performing ML engineering team, and drive technical innovation across the Wealth Management data domain.
The ideal candidate will have:- Expertise in deploying ML models and integrating WM data with cutting-edge ML solutions
- A strong background in machine learning, software development, and technical leadership
- A proven track record of delivering high-impact solutions that meet complex business needs
- Deep understanding of modern data stacks, cloud computing, and MLOps practices
- Ability to shape organizational ML strategy, provide technical direction, and lead cross-functional initiatives
You will play a pivotal role in building and scaling our ML capabilities while partnering with IT and business stakeholders to assess, research, and resolve critical business challenges through technology solutions.
What will you do?Team Leadership & Management- Manage and lead a team of ML engineers and data engineers, providing technical guidance, mentorship, and career development
- Foster a high-performing culture of innovation, collaboration, and continuous learning
- Conduct performance evaluations and provide constructive feedback to team members
- Hire and build diverse, talented teams aligned with organizational goals
Technical Strategy & Direction- Own end-to-end ML project delivery, from conception through production deployment and optimization
- Define and communicate technical roadmap and architecture for ML initiatives aligned with business objectives
- Provide technical direction and set standards for ML development practices, code quality, and MLOps
- Make critical technical decisions that balance innovation, scalability, and risk management
- Partner with architects, product managers, and business leaders to evaluate use cases and align ML initiatives with company goals
ML Development & Deployment- Design, build, and deploy scalable machine learning models that integrate WM data with advanced ML algorithms
- Oversee end-to-end ML pipelines ensuring seamless integration with applications and data platforms
- Establish best practices for model development, validation, monitoring, and continuous improvement
- Collaborate with data engineers to ensure efficient data collection, preparation, and feature engineering
MLOps & Quality Assurance- Establish and maintain coding standards and best practices across the ML engineering team
- Set up processes to ensure high-quality code through regular reviews and compliance with RBC's standards
- Build and maintain comprehensive documentation of ML architectures, models, pipelines, and processes
- Design monitoring and metrics systems to meet Service and Operational Level Agreements (SLAs)
Cross-Functional Collaboration- Act as primary technical liaison with multiple RBC teams, stakeholders, executives, and third-party vendors
- Collaborate with Agile teams, product owners, software engineers, and business stakeholders
- Communicate complex ML concepts to non-technical audiences and translate business needs into technical solutions
- Drive organizational alignment on ML priorities and technical capabilities
Continuous Learning & Innovation- Stay at the forefront of emerging ML technologies, cloud advancements, and industry best practices
- Share knowledge with teams and drive adoption of new techniques to improve existing systems
- Contribute to thought leadership within RBC and the broader ML community
What do you need to succeed?Must Have- 7+ years of hands-on experience in machine learning development with 3+ years in a leadership or mentorship role
- Expertise in deploying ML models and integrating data systems with ML solutions in production environments
- Strong programming skills in Python and Java; experience with REST APIs, GraphQL, and ETL pipeline development
- Expert-level proficiency in cloud platforms: AWS and/or Azure, with OpenShift containerization experience
- Deep understanding of DevOps practices: CI/CD pipelines, containerization (Docker, Kubernetes), monitoring tools
- Experience with ML platforms and tools (e.g., Helios) for model deployment and orchestration
- Solid database knowledge: SQL Server, Snowflake, or similar enterprise data platforms
- Proven ability to manage and mentor engineering teams with demonstrated impact on team performance and growth
- Strong understanding of software development principles: design patterns, testing, deployment strategies
- Excellent communication and leadership skills with the ability to influence and collaborate across business and technical teams
- Strong understanding of application implementation requirements, including risk, privacy, and compliance
- Proven ability to lead complex, end-to-end projects in fast-paced, collaborative environments
Nice to Have- Understanding of IT Standards, Methodologies, CMM & audit requirements
- Financial institution and Wealth Management domain knowledge
- Experience with GenAI and advanced ML techniques (NLP, deep learning, reinforcement learning)
- Knowledge of modern data platforms and architectures (data lakes, data warehouses, streaming platforms)
- Experience with Agile and Scrum methodologies
What's in it for you?- A comprehensive Total Rewards Program including bonuses, flexible benefits, and competitive compensation
- Leaders who support your development and growth through coaching and strategic opportunities
- The ability to make a significant, lasting impact on RBC's ML strategy and technical capabilities
- Work in a dynamic, collaborative, progressive, and high-performing team
- A world-class training program in financial services
- Flexible work/life balance options
- Opportunities to lead challenging, high-visibility projects
- Opportunities to take on progressively greater responsibilities and strategic influence
- Access to a variety of career advancement opportunities across RBC's business units and geographies
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Job SkillsBig Data Management, Data Mining, Data Science, Deep Learning, Machine Learning (ML), Predictive Analytics, Programming Languages
Additional Job DetailsAddress:RBC CENTRE, 155 WELLINGTON ST W:TORONTO
City:Toronto
Country:Canada
Work hours/week:37.5
Employment Type:Full time
Platform:TECHNOLOGY AND OPERATIONS
Job Type:Regular
Pay Type:Salaried
Posted Date:2026-08-07
Application Deadline:2026-08-31
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
