Join the team redefining how the world experiences design.

Hey, g'day, mabuhay, kia ora,你好, hallo, vítejte!

Thanks for stopping by. We know job hunting can be a little time consuming and you're probably keen to find out what's on offer, so we'll get straight to the point. 

Where and how you can work

Our flagship campus is in Sydney, with a second campus in Melbourne and co-working spaces in Brisbane, Perth, Adelaide, and Auckland, NZ. You have flexibility in how and where you work — whether that's from one of our spaces, from home, or a mix of both. This role is remote-friendly within Australia or New Zealand, so you can choose the setup that empowers you and your team to do your best work.

About the Group/Team

The Video AI Engine team sits within the Video group in the Design Experience supergroup. We build the infrastructure that connects advanced AI research with delightful product experiences in Canva’s video editor. From video segmentation and effect orchestration to scalable ML serving, we’re enabling users to create cinematic stories, automatically and effortlessly.

About the Role/Specialty

As a Senior Machine Learning Engineer, you’ll bridge the gap between cutting-edge research and large-scale production. You’ll help productionize novel models, optimize inference performance, and work side-by-side with cross-functional teams to deploy delightful, real-time experiences in Canva’s editor. You’ll bring curiosity, rigour, and craft to an area that’s rapidly evolving, and deeply meaningful for our users.

What you’ll do (responsibilities)

• You’ll productionize video-based ML models, enabling scalable, reliable deployment
• You’ll develop high-performance inference pipelines for near real-time use in Canva’s editor
• You’ll experiment with and evaluate model effectiveness for diverse video editing use cases
• You’ll collaborate with AI researchers to translate novel techniques into deployable video tools
• You’ll contribute to scalable ML infrastructure and model serving and experimentational frameworks
• You’ll participate in roadmap discussions, engineering reviews, and planning cycles
• You’ll be hands-on with model evaluation, optimization, and continuous improvements

What we're looking for

• Experience deploying ML models into production, ideally for video, vision, or generative applications
• Proficiency in Python and deep learning frameworks (e.g., PyTorch, Torch)
• Strong systems knowledge, including working with inference pipelines and performance optimization
• Familiarity with ML lifecycle tooling—experiment tracking, monitoring, deployment
• Collaborative approach and ability to work across product, research, and infrastructure teams
• A user-focused mindset and drive to create magical experiences powered by ML