
RBC Amplify Program
Summer 2021
Not your typical internship.
Amplify is an intensive summer innovation program that lets you put your skills to the test while building a product that could disrupt our company and beyond. As an Amplifier, you’ll work in a team of four and get assigned a bold business challenge, developing a solution and pitching it continuously throughout the summer. Join our community, grow your network, and kickstart your career with RBC Amplify.
International Program
Recruitment for our International Program is underway. Stay tuned and check back in January 2021 for a second round of postings for our remaining roles!
What's in it for you?

Leave your mark
When you build an Amplify product, it’s not just a student project. It’s the real deal. You’ll be sponsored by senior executives with meaningful problems – and they’re looking to you to solve them.

Win as a team
Your team has the freedom to set the vision and strategy for your product. You’ll have plenty of support and mentorship, but it’s up to the four of you to build something users love.

Never stop learning
Amplify unlocks opportunities to upgrade your skills and learn something new from our very best. You’ll hone your craft (whether it be business or technical), meet dozens of subject-matter experts, and become a startup pitch master.
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“We built a product from scratch and it was Data Science heavy so we focused on leveraging Machine Learning and NLP techniques to develop the core model of our solution!”
Seher Sahrin, Developer

“We had the opportunity to learn new skills like Container Orchestration Technology, Microservice Design Techniques, and Security Principles. I always felt supported along the way and enjoyed the experience.”
Russell Goldman, Developer

“I learned how to deploy an app, specifically a MySQL database to Openshift. I’ve never worked with anything like it before and it was cool to deploy these real systems myself.”
Mathusan Thanabalasingam, Data Scientist
slide 1 of 3 “We built a product from scratch and it was Data Science heavy so we focused on leveraging Machine Learning and NLP techniques to develop the core model of our solution!” Seher Sahrin, Developer