What is the chance?
We’re looking for a Lead AI/ML Software Engineer to drive innovation at the intersection of AI / Machine Learning and financial services. You’ll be responsible for owning and delivering projects end to end – from design, development, testing and release of the product to production. In addition to software development tasks, the role will also include machine learning tasks such as data pre-processing and exploration, building and scaling ML algorithms and pipelines and deployment and monitoring of production systems. At RBC Digital, you’ll be joining a team that works on world class digital experiences and has access to rich and massive datasets and offers the computational resources to support cutting‑edge machine learning development.

Responsibilities

- Design, develop, and maintain scalable backend components and ML models in support of Online Banking and digital channel applications.
- Participate in code reviews, testing, and documentation to ensure best practices and code quality.
- Apply software engineering and ML best practices to architect robust, scalable machine learning systems.
- Troubleshoot and resolve technical issues in a timely manner.
- Work in an agile environment, actively participating in sprint planning, stand‑ups, and retrospectives.
- Strong written and verbal communication skills, with the ability to work cross‑functionally and influence stakeholders.

Qualifications

- PhD or Master’s degree in Computer Science, Machine Learning, or equivalent hands‑on experience.
- Five or more years building and deploying Machine Learning models in production for real business problems.
- Advanced proficiency in Java/Python, 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 (OpenShift Container Platform / OCP4 or Kubernetes).
- Proficiency with AI‑assisted software development tools (e.g., GitHub Copilot, Windsurf AI, Anthropic Claude Code).
- Exceptional verbal and written communication skills with proven ability to collaborate effectively across cross‑functional teams (business, engineering, model risk management).

Nice to Have

- 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.

Benefits

- A comprehensive Total Rewards Program including bonuses and flexible benefits.
- Leaders who support your development through coaching and managing opportunities.
- Ability to make a difference and lasting impact.
- Work in a dynamic, collaborative, progressive, and high‑performing team.
- Access to a variety of job opportunities across business and geographies.

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📌 Lead AI/ML Software Engineer (Toronto)
🏢 RBC
📍 Toronto