Senior Machine Learning Research Engineer at RBC Global Asset Management

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

26 Feb, 26

Salary

0.0

Posted On

28 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Analytical Thinking, Decision Making, Detail-Oriented, Machine Learning, Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations

Industry

Description

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 Senior Machine Learning Research Engineer who’s excited by the opportunity of being at the forefront of applying machine learning technology to challenging problems. As a Senior ML Research Engineer in the applied research team, you’ll be part of a collaborative group who 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. Your responsibilities include: Lead development of 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. You’re our ideal candidate if you have: A master’s or PhD degree in computer science, mathematics, physics, economics or equivalent; 5+ years of applied machine learning experience as an individual contributor driving projects; 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 Tensorflow; 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. 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 RBC Borealis 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. Inclusion and Equal Opportunity Employment 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. Job Skills Analytical Thinking, Decision Making, Detail-Oriented, Long Term Planning, Machine Learning, Product Development Design, Programming Languages, Quantitative Research, Research and Development Operations, Research Documents Additional Job Details 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: 2025-11-27 Application Deadline: 2026-02-23 Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above Inclusion and Equal Opportunity Employment At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all. Join our Talent Community Stay in-the-know about great career opportunities at RBC. Sign up and get customized info on our latest jobs, career tips and Recruitment events that matter to you. Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

Responsibilities

Lead the development of machine learning-based software solutions and collaborate with business stakeholders to prototype machine-learning solutions rapidly. Support projects with thorough documentation, design decisions, and capabilities.