Location: Toronto

What's the opportunity?

Borealis AI is a team of researchers and developers dedicated to solving today’s leading problems in machine learning and artificial intelligence. Our researchers are dedicated to pushing the boundaries of theoretical and applied science, while our development team transforms state-of-the-art technologies and algorithms into impactful products with the potential to reach millions of people.

We’re looking for an enthusiastic candidate to fill the full-time role of Administrative Coordinator for our Toronto office.

What will you do?

  • Ensure organizational effectiveness and efficiency within the office.
  • Assist in coordinating team and office events.
  • Contribute to the implementation of operational improvements in order to streamline procedures.
  • Provide support in organizing meetings, workshops, and conferences.
  • On/off-board new employees and contractors, including form submittals and asset management.
  • Maintain the condition of the office and arrange for supplies and general upkeep.

What do you need to succeed?

  • Recent graduate in business administration, business management or relevant experience.
  • Strong interpersonal relationship skills.
  • Ability to work efficiently and accurately with minimal supervision.
  • Excellent organizational and time management skills.
  • Ability to multitask and prioritize workload to meet deadlines.
  • Experience in an academic, research or start-up environment preferred.

How to apply

Please email your resume to mi.research@borealisai.com.

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, Edmonton, Montreal, Waterloo and Vancouver, we support open 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.