About the job
Become a pivotal member of a team transforming the global design landscape.
Hello, g'day, mabuhay, kia ora, 你好, hallo, vítejte!
Welcome! We understand that job searching can be time-consuming, so let's get straight to the details.
About the Team
We are Canva Grow, one of Canva’s newest product groups, established through the acquisition of MagicBrief. Our mission is to create the platform within Canva that amalgamates creativity, data, and insights - empowering businesses to thrive through superior advertising.
Effective advertising connects individuals with things they adore. Our aim is to enable every business to craft ads that are not only impactful and creative but also respectful of the audience's attention. We are rapidly scaling, combining the nimbleness of a startup with the robust support of Canva’s global infrastructure.
You will be joining the Inspire & Create team, spearheading product development at the crossroads of publishing systems, creative performance, and integrated ad platforms. Your influence will extend beyond a single team; as our inaugural Machine Learning Engineer in Grow, you will shape the entire feedback loop across the group - your contributions will affect the entire customer journey from Inspire → Create → Publish → Insights → Recommend → Inspire.
Responsibilities in this Role:
As Canva continues to scale, change is woven into our fabric, and we see it as part of the excitement. Here’s a glimpse of what you’ll be working on, though your responsibilities may evolve:
Developing, testing, and deploying machine learning-driven features that enhance our ad generation experiences.
Designing scalable ML pipelines in partnership with our platform teams.
Collaborating closely with product managers, designers, and engineers to align on user needs and product vision.
Executing experiments to validate assumptions and enhance model effectiveness.
Contributing to shared ML infrastructure and best practices at Canva.
Staying updated with state-of-the-art developments and finding ways to apply them at scale.

