Description of Organization
Royal Bank of Canada (RBC) is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance. RBC’s success comes from the 98,000+ employees who leverage their imaginations and insights to bring the bank’s vision, values and strategy to life so it can help its clients thrive and communities prosper. As Canada’s biggest bank and one of the largest in the world, based on market capitalization, RBC has a diversified business model with a focus on innovation and providing exceptional experiences to its 19 million clients in Canada, the U.S. and 27 other countries. Learn more at rbc.com.
Problem area
Build a distributed inference platform that aggregates idle computing power from employee devices to support scalable, cost-efficient AI model deployment on enterprise infrastructure.
Main objectives
Build a distributed compute pooling system that aggregates idle device capacity across RBC's enterprise fleet to enable cost-efficient, scalable AI model inference deployment.
Scope of work
- Literature review
- Model + prototype development
- Model performance testing
- Final Report
Deliverables
- Report
- Resources
- New protocols/procedures
- MVP, demo video, code & documentation, performance measurements & analysis, and architecture diagram & description
Frequency
- Bi-weekly
Skills and training required
- Agile principles
- Research & analytical skills including leveraging GenAI
- Presentation skills
Resources required
Simulated datasets, SME expertise provided by RBC project leaders, specific software, and more to be determined.
NDA or a commercialization agreement for this project?
Yes