Lead AI/Machine Learning Engineer (Mississauga)

Overview

You will be a Lead Machine Learning Engineer on the RBC Insurance Active Data Platform team. This role leads AI initiatives, development and deployment of machine learning models, mentorship and cross‑functional collaboration.

Responsibilities

• Technical Leadership: lead a team of machine learning engineers and data scientists, provide technical guidance and oversight.
• Collaboration: partner with Agile project teams, product managers, owners, software engineers, and stakeholders to evaluate use cases and align ML initiatives with company goals.
• MLOps: design, build, and deploy scalable machine learning models and algorithms that address business needs, focusing on performance and reliability.
• Oversee end‑to‑end machine learning pipelines to ensure integration with applications.
• Collaborate with data engineers to ensure efficient data collection and feature engineering pipelines.
• Documentation: establish and maintain standards and documentation of architecture, models, pipelines, and development processes.
• Code reviews and quality assurance to meet RBC coding standards.
• Operations: maintain metrics and monitoring to meet SLAs, build maintainable products with minimal incidents.
• Emerging technologies: stay current with advances in machine learning and related technologies, share knowledge and apply to improve systems.

Qualifications

• Strong programming skills in Python, Java or C++.
• 3+ years hands‑on experience in machine learning development and leading teams.
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps tools.
• Experience with DevOps practices such as CI/CD, Docker and Kubernetes.
• Strong understanding of software development principles, design patterns, testing and deployment.
• Strong understanding of data and AI/ML space, risk, privacy and compliance.
• Excellent communication and leadership skills, ability to work effectively with cross‑functional teams.
• Graduate in science, mathematics, statistics or engineering.
• Preferred: experience in data and AI/ML space and knowledge of application implementation requirements.

Benefits

A comprehensive Total Rewards Program including bonuses, flexible benefits, competitive compensation, commissions and stock where applicable. Flexible work/life balance, progressive training program, opportunities to take on greater accountabilities and build client relationships.