Machine Learning Engineering Lead
What's the opportunity?
We’re looking for an Engineering Manager to lead our Equities Returns Prediction team, being at the forefront of machine learning technology and working on extremely challenging problems.
As a Machine Learning Engineering Lead, you’ll be responsible for owning and delivering a project end to end – everything from data pre-processing to implementing machine learning training pipelines and deploying inference in a production environment. You’ll be directly managing a team of machine learning engineers, responsible for strategic planning, execution and delivery. You will provide your team with technical leadership and mentorship. You will work along other engineering leads across Borealis AI. As a people manager you will be responsible for growing your team and fostering career growth of the engineers.
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. Each project we take on is like a small start-up, imagine working in a start-up that can immediately impact millions of customers! You can find out more about our work at www.borealisai.com.
Your responsibilities include:
- Lead and directly manage a team of 4 engineers, being responsible for planning execution and delivery of ML systems;
- Establish high standards and share knowledge in performance, scalability, enterprise system architecture, and engineering best practices;
- Establish and maintain collaboration with research and business teams to converge on the best solutions;
- Extending prototypes into fully functional, polished solutions ready for internal and/or external use;
- Grow and develop the team, helping each team member advance in their career.
You're our ideal candidate if you:
- Have 7+ years of experience delivering software projects to production;
- Have experience managing a team of engineers;
- Have experience developing modular, robust, scalable software in a modern programming language;
- Experience working with business, product and other technical teams;
- Experience with scaling and performance of large systems;
- Have led the full lifecycle of software product development including the successful deployment of products to production;
- Experience taking a leading role in building complex software products, fostering career growth of software engineers, and establishing software engineering best practices within your team;
- Have background in machine learning or a related field;
- Experience with Capital Markets or any financial domain is a big 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 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
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.