Senior Machine Learning Engineer – Brand Templates

Role Overview

• Owning the end-to-end ML lifecycle from problem framing through to production deployment and iteration
• 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
• 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)
• 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

Requirements

• 5+ years of hands-on experience building and deploying ML-powered features in production environments
• Proficient with Python and ML frameworks such as PyTorch or TensorFlow
• Strong experience with NLP/NLU techniques — including working with LLMs, embeddings, semantic search, prompt engineering, RAG, or fine-tuning
• Experience with document understanding, layout analysis, or structured data extraction from semi-structured formats
• Experience building information retrieval, ranking, or recommendation systems
• Skilled across the ML lifecycle: data processing, model training, evaluation, deployment, and monitoring
• Experience designing and running A/B experiments to measure feature impact
• Comfortable operating independently as the ML technical lead within a product team, while collaborating deeply with engineers, PMs, and designers
• Strong product mindset — you prioritise ML solutions that improve user experience and drive measurable business outcomes
• Committed to scalable, maintainable ML systems with clear metrics and impact tracking
• 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

Tech Stack

• Microservices
• Python
• PyTorch
• Tensorflow

Benefits

• Equity packages
• we want our success to be yours too
• Inclusive parental leave policy that supports all parents & carers
• An annual Vibe & Thrive allowance to support your wellbeing, social connection, office setup & more
• Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally