Senior Machine Learning Engineer - AI Evaluation Platform (AU remote)
CanvaSydney,Posted 1 April 2026
Tech Stack
Job Description
About the Group/Team
We are part of the Generative AI Supergroup, specifically within the AI Platform group, where we’re building the foundations that power Canva’s AI-first future. Our team focuses on creating scalable, reliable infrastructure and systems that enable teams across Canva to build, evaluate, and deploy machine learning models with confidence. Within the Evaluations Platform, we play a critical role in ensuring that every AI experience meets Canva’s high standards for quality, safety, and usability. We collaborate closely with ML engineers, researchers, and product teams to define what “great” looks like for AI—and build the systems to measure it.
About the Role/Specialty
As a Senior Machine Learning Engineer, you’ll bring strong technical expertise and a platform mindset to design and build evaluation systems that scale across Canva’s AI ecosystem. You’ll work on complex challenges such as surfacing insights from both human-in-the-loop and automated evaluations across a wide range of mediums and product areas. You’ll operate with a high level of autonomy, contributing to technical direction within the team while collaborating with cross-functional partners. This role is perfect for someone who thrives on solving ambiguous problems, enjoys working at the intersection of ML and platform, and is motivated by delivering impactful, user-facing AI experiences.
What you’ll do (responsibilities)
You’ll design and build scalable evaluation systems for machine learning models, including generative AI
You’ll collaborate with cross-functional teams to integrate evaluation into the ML lifecycle
You’ll improve experimentation velocity by enabling reliable and automated evaluation workflows
You’ll contribute to technical design discussions and help shape the team’s direction
You’ll identify opportunities to improve systems, tooling, and processes across the AI Platform
You’ll mentor peers and contribute to a strong engineering culture
What we're looking for
Please note, this is not a model building role, we work on a common core of platform functionality that is generalisable across domains, and often that means we skew more towards ML infrastructure or even backend service development problems than pure ML. This is role is also not a stepping stone to adjacent model development roles. You’re an experienced Machine Learning Engineer who combines strong technical depth with a pragmatic, product-focused mindset. You enjoy tackling complex, ambiguous problems and turning them into scalable, reliable systems. You likely have experience working with ML systems in production, including model evaluation, experimentation, or platform tooling. You’re comfortable collaborating with cross-functional teams and communicating technical concepts clearly. Most importantly, you’re motivated by building high-quality AI experiences that make a real impact for users around the world.  
What the candidate will learn and how will they develop at Canva:
Deep expertise in building and scaling ML evaluation systems in a world-class AI environment
Exposure to cutting-edge Generative AI technologies and large-scale ML systems
Opportunities to influence platform-level decisions impacting multiple teams
Growth in technical leadership, stakeholder management, and cross-functional collaboration
The chance to work on meaningful problems that impact millions of users globally
Don't tick all the boxes? Don't worry about that - nobody does!  
We’d still love to hear from you! At Canva, we know that great engineers come from a variety of backgrounds, and we value passion, curiosity, and a willingness to learn just as much as specific experience. If you're excited about this role but don’t tick every box, we encourage you to apply, you might a great fit in ways you didn’t expect!
What's in it for you?
Achieving our crazy big goals motivates us to work hard - and we do - but you'll experience lots of moments of magic, co ... (truncated, view full listing at source)
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