Senior Machine Learning Software Engineer

Job Description

What's the opportunity?At RBC Borealis, you’ll be joining a team of leading researchers and software engineering specializing in machine learning. You will have access to rich and massive datasets, and to computational resources to support novel product development touching machine learning areas such as generative AI, natural language processing, and time series analysis.

We’re looking for an enthusiastic software developer who’s excited by the opportunity of working on challenging problems at the intersection of machine learning and the financial services industry. As a Senior Machine Learning Software Engineer, you’ll be responsible for owning and delivering a project end to end – everything from data pre-processing and exploration, to building and scaling ML algorithms and pipelines, to deployment and monitoring of production systems.

At RBC Borealis, you’ll be joining a team that works directly with leading researchers in machine learning, has access to rich and massive datasets, and offers the computational resources to support cutting-edge machine learning R&D.
Your responsibilities include:

Lead development of machine learning-based software solutions throughout the research and product development lifecycle;

To play a key role in the design and development of Borealis’ machine learning products;

To partner with RBC Borealis’s research and product teams to ensure the seamless delivery of these products;

To apply engineering and data best practices to build robust and scalable large-scale machine learning software systems;

To support projects with thorough documentation, design decisions, and technical advisory.

You're our ideal candidate if you have:

A degree in Computer Science, Software Engineering, or equivalent field;

7+ years of experience as a software engineer;

Experience building modular and robust software systems in Python or similar language;

Knowledge of professional software engineering best practices for the full software development life cycle, including testing methods, coding standards, code reviews and source control management;

Experience working across the entire ML research and product lifecycle from prototyping to production is a plus;

Experience building microservices, data pipelines and using relational and non-relational databases is a plus;

Experience working with data science tooling and deep learning frameworks is a plus;

Experience with Dev Ops engineering (CI/CD pipelines, observability, containers etc) is a plus.

What's in it for you?

Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

Leaders who support your development through coaching and managing opportunities;

Ability to make a difference and lasting impact from a local-to-global scale.

About the AI Group:
RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations.

The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery — ensuring RBC remains at the frontier of AI-enabled value creation.