Lead AI​/ML Software Engineer

Lead AI/ML Software Engineer

The Solution Acceleration & Innovation (SA&I) team within Personal Banking strives to position RBC as a Global Leader in innovation with a focus on emerging opportunities and technologies. SA&I is a critical horizontal function that supports multiple business lines by building new products and capabilities, with a primary focus on emerging technologies, payments, security, data and privacy, and Artificial Intelligence (AI).

We are a multi-disciplinary team with work spaces in Toronto, ON and Orlando, FL consisting of cutting-edge technology researchers and experts, strategists, product managers, project managers, security and payments specialists, developers, and designers. This unique mix enables us to not only generate forward-looking product concepts but also to deliver and launch products in the market - strengthening RBC's leadership position.

We’re looking for a Lead AI/ML Software Engineer to drive innovation at the intersection of AI / Machine Learning and financial services. In this role, you’ll own end-to-end AI solution delivery – from data preprocessing and exploration through ML algorithm development, pipeline scaling, and production system deployment and monitoring. You’ll join SA&I’s team of technologists reimagining the future of the Personal Bank at RBC.

• Design and build cutting-edge ML models in support of Agentic Commerce solutions.
• Lead the development of Personal Banking’s machine learning products across the full lifecycle - from ideation and proof-of-concept through development, deployment, and production monitoring.
• Collaborate with product and stakeholders to ensure the seamless delivery and integration of AI solutions.
• Apply software engineering and ML best practices architect robust, scalable machine learning systems.
• Provide comprehensive documentation and articulate design decisions and technical rationale to support team understanding and knowledge transfer.
• Stay current with emerging AI/ML technologies, mentor team members, and champion a culture of innovation and continuous learning.

• PhD or Master’s degree in Computer Science, Machine Learning, or equivalent hands‑on experience.
• Exceptional verbal and written communication skills with proven ability to collaborate effectively across cross‑functional teams (business, engineering, model risk management).
• Five (5) or more years building and deploying Machine Learning models in production for real business problems.
• Advanced proficiency in Python (preferred) and/or other programming languages, with demonstrated ability to write production-grade code and documentation.
• Advanced proficiency with large language model architectures, including inference (Tensorflow or Pytorch), fine‑tuning, and model deployment.
• Strong understanding and work experience with retrieval‑augmented generation (RAG) systems, agentic systems, orchestration frameworks, context and memory management, and tool/skills integration patterns.
• In‑depth knowledge of embeddings, re‑rankers, and vector databases.
• Expertise in ML experimentation, model evaluation, and production observability.
• Proven experience building and deploying RESTful APIs for ML model serving (FastAPI, Flask).
• Demonstrated proficiency with MLOps practices, including model serving, monitoring, CI/CD pipelines for ML systems, and containerized workload deployment (Open Shift Container Platform / OCP4 or Kubernetes).
• Proficiency with AI‑assisted software development tools (e.g., Git Hub Copilot, Windsurf AI, Anthropic Claude Code).

• Experience with Small Language Models (SLMs) for on‑device inference, domain specialization through fine‑tuning, or Reinforcement Learning applications.
• Track record of adopting and leveraging AI‑driven solutions to enhance productivity, automate routine tasks, and drive efficiency.
• Demonstrates curiosity about emerging AI capabilities and a thoughtful approach to applying them for enhanced client outcomes.
• Experience in managing, mentoring, or coaching team members and empowering junior engineers to grow and succeed.

• Ability to make a difference and lasting impact
• Work in a dynamic, collaborative, progressive, and high‑performing team
• Opportunities to do challenging work
• Consistent access to training, education and professional development opportunities
• Be a part of a collaborative team that brings outside‑in thinking to RBC