Research Engineer

Overview

What’s the opportunity?

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

We’re looking for an enthusiastic Machine Learning Research Engineer who’s excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As an ML Research Engineer in the applied research team, you’ll be part of a collaborative group that aims to deliver 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.

The goal is to understand the needs of our business partners and bring to life these unique and efficient solutions that can only be achieved through the use of machine learning.

• Building machine learning-based software solutions;
• Collaborating with business stakeholders 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;
• Supporting projects with thorough documentation, design decisions, and capabilities.

• A master’s or PhD degree in computer science, mathematics, physics, economics or equivalent;
• 2+ years of applied machine learning experience in a high-responsibility, minimal-supervision environment;
• Experience with writing modular, robust, scalable software in Python 3.x;
• Expertise in a few of the following areas: deep learning, natural language processing, information retrieval;
• Experience with deep learning packages such as PyTorch, JAX, or Tensor Flow;
• 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;
• Strong communication skills and a collaborative attitude.

• 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.

RBC Borealis, an 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.

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.

Note:

Applications will be accepted until the stated deadline date above.

Address: 777 BAY ST, TH 27:

TORONTO

City:
Toronto

Country:
Canada

Work hours/week: 37.5

Employment Type:

Full time

Platform: TECHNOLOGY AND OPERATIONS

Job Type: Regular

Pay Type:

Salaried

Posted Date:

Final date to receive applications: