Location: Toronto, Vancouver

What’s the opportunity?

Borealis AI is a team of researchers and developers dedicated to solving today’s leading problems in machine learning and artificial intelligence. Our researchers are dedicated to pushing the boundaries of theoretical and applied science, while our development team transforms state-of-the-art technologies and algorithms into impactful products with the potential to reach millions of people.

We’re looking for an enthusiastic software developer who’s excited by the opportunity of being at the forefront of machine learning technology, and working on extremely challenging problems. As a Research Engineer, you’ll be part of a collaborative team delivering AI projects end to end – everything from data pre-processing and exploration, to prototyping novel algorithmic solutions, to software implementations of machine learning-based products. You will function as a bridge between research and development teams to help extend research prototypes into implemented products.

At Borealis AI, 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 ongoing development in areas such as reinforcement learning, unsupervised learning and computer vision. You can find out more about our research areas at borealisai.com.

Your responsibilities include:

  • Building machine learning-based software solutions;
  • Collaborating with researchers to prototype machine-learning solutions rapidly;
  • Conducting comparisons to existing algorithms and baselines;
  • Reviewing, extending, and optimizing prototype solutions;
  • Collaborating with the engineering team to integrate algorithms into products;
  • Developing reusable internal tools to facilitate research prototyping; and
  • Supporting projects with thorough documentation, design decisions, and capabilities.

You’re our ideal candidate if you have:

  • A master’s or PhD degree in computer science, software engineering, or equivalent, with research in an AI sub-field;
  • 2+ years of applied machine learning experience in a high-responsibility, minimal-supervision environment;
  • Experience with writing modular, robust, scalable software in one of the major languages such as Python 3.x, C++, or Java;
  • Familiarity with the Unix command line and bash scripting;
  • Solid understanding and experience in two or more of the following areas: deep learning, NLP, time series, computer vision, reinforcement learning;
  • Experience with deep learning packages such as PyTorch, Keras, and Tensorflow;
  • Exposure to distributed computing using CPUs and GPUs;
  • 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; and
  • Strong communication skills and a collaborative attitude.

What's in it for you?

  • Become part of a team that thinks progessively 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 

How to apply:

Please email your resume to mi.research@rbc.com and include where you heard about this opportunity.

About Borealis AI

Borealis AI, a RBC Institute for Research, is a curiosity-driven research centre dedicated to achieving state-of-the-art in machine learning. Established in 2016, and with labs in Toronto, Montreal, Waterloo and Vancouver, we support academic collaborations and partner with world-class research centres in artificial intelligence. With a focus on ethical AI that will help communities thrive, our machine learning scientists perform fundamental and applied research in areas such as reinforcement learning, natural language processing, deep learning, and unsupervised learning to solve ground-breaking problems in diverse fields.

Inclusion and Equal Opportunity Employment
