Senior Machine Learning Engineer - Brand Templates (AU remote) at Canva

About the Group/Team We're the Brand Templates team within the Branded Experience (BEX) group. Our mission is to make it effortless for organisations to create, manage, and scale on-brand content — ensuring every design stays consistent whether it's created by one person or thousands across an enterprise. Brand Templates power the backbone of Canva's enterprise offering. We enable brand designers and administrators to lock down design guardrails while giving end users the freedom to customise within those boundaries. These templates are used by organisations to produce everything from social posts to pitch decks — at scale and on brand. We're now investing heavily in AI to make Brand Templates smarter — and the problems are genuinely interesting. We're building systems that extract and understand layout structure from Canva's design format (CDF) to enable on-brand design generation. We're developing ranking and recommendation models that suggest high-performing designs to be converted into Brand Templates. And we're working on brandification at scale — automatically transforming marketplace templates to conform to an organisation's brand guidelines so they can be published as Brand Templates. This is a greenfield ML opportunity at the intersection of document understanding, generative AI, information retrieval, and product-facing ML — with direct impact on Canva's enterprise growth. About the Role As a Senior Machine Learning Engineer on Brand Templates, you'll be the ML technical lead for the team — owning the end-to-end ML lifecycle from problem framing through to production deployment and iteration. You'll work closely with product managers, product designers, backend engineers, and platform teams to build ML-powered features that make Brand Templates more discoverable, more relevant, and more intelligent. This is not a research role. You'll be building production ML systems that serve enterprise customers at scale, with a strong emphasis on shipping, measuring impact, and iterating fast. What you'd be doing in this role As Canva scales change continues to be part of our DNA. But we like to think that's all part of the fun. So this will give you the flavour of the type of things you'll be working on when you start, but this will likely evolve. At the moment, this role is focused on: • Developing ranking and recommendation models that identify high-performing team designs and suggest them as candidates for conversion into Brand Templates • Building brandification pipelines at scale — automatically transforming marketplace templates to conform to an organisation's brand guidelines (colours, fonts, logos, imagery style) so they can be published as Brand Templates • Building layout extraction and understanding systems that parse Canva's design format (CDF) to identify structural patterns, element relationships, and design intent — enabling downstream on-brand design generation • Designing and productionising LLM-based pipelines for generating structured metadata (intent descriptions, content classifications) across large volumes of brand templates • Running experiments (offline and online) to validate model effectiveness and measure impact on user outcomes • Collaborating with the Templates Platform team and cross-functional partners to define data contracts, APIs, and integration patterns for ML features • Contributing to the broader Brand System AI vision — exploring how ML can reason about brand guidelines, design constraints, and content structure to assist enterprise users • Establishing ML best practices within the team: experiment tracking, model evaluation frameworks, monitoring, and documentation You're probably a match if: • You have 5+ years of hands-on experience building and deploying ML-powered features in production environments • You are proficient with Python and ML frameworks such as PyTorch or TensorFlow • You have strong experience with NLP/NLU techniques — including working with LLMs, embeddings, semantic search, prompt engineering, RAG, or fine-tuning • You have experience with document understanding, layout analysis, or structured data extraction from semi-structured formats • You have experience building information retrieval, ranking, or recommendation systems • You are skilled across the ML lifecycle: data processing, model training, evaluation, deployment, and monitoring • You have experience designing and running A/B experiments to measure feature impact • You are comfortable operating independently as the ML technical lead within a product team, while collaborating deeply with engineers, PMs, and designers • You have a strong product mindset — you prioritise ML solutions that improve user experience and drive measurable business outcomes • You are committed to scalable, maintainable ML systems with clear metrics and impact tracking • You follow disciplined coding practices, actively participate in code reviews, and set best-practice standards for peers Highly desirable: • Experience with layout understanding, document parsing, or structured extraction from design/document formats • Familiarity with embeddings and vector databases • Experience with enterprise or B2B product contexts where brand consistency and governance matter • Familiarity with GenAI platforms (e.g. OpenAI, Anthropic) • Experience with microservices architectures and large monorepos • A Master's or PhD in a machine learning discipline