Machine Learning Software Engineer II

Key Skills

Continuous Integration & Continuous Delivery - CI/CD, Deep Learning, DevOps, Machine learning techniques, Python Programming

Job Description

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 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:

• To build cutting edge ML 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:

• 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 DevOps engineering (CI/CD pipelines, observability, containers etc) is a plus.

 What's in it for you?

• Be part of a dynamic & flexible working environment;
• Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
• 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 RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.