Staff ML Engineer

Job Description

What 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-pe