Senior Machine Learning Engineer - Integrations (AU remote) at Canva

About the team We aim to build the world’s richest Ecosystem of apps for visual design and communications that supercharge Canva’s ability to meet the diverse needs of a billion users and drive Canva’s MAU growth. With the proliferation of innovations in generative AI and as large organizations have increasingly complex workflows to manage their designs, Canva is well poised to become the platform that simplifies access and discovery of services related to visual design. We are already working with hundreds of developers to enable access to these exciting products with our Apps SDK and Canva public REST API! As one of the groups in Ecosystem, the Integrations and Solutions Group builds Canva's AI integration layer — the infrastructure that connects Canva's design capabilities to the world's leading AI assistants. Our teams own the MCP platform, AI-optimised tools and APIs, evaluation frameworks, and the agent architecture that powers millions of AI-driven design interactions. We work directly with partners like OpenAI, Anthropic, and Google, and we're in the middle of a strategic shift from protocol-first integrations toward intelligent, Canva-hosted design agents. As a Senior Machine Learning Engineer, you'll play a key role in shaping how AI platforms experience Canva — ensuring our tools are reliable, our integrations are measurable, and our agent architecture evolves to meet the needs of a rapidly changing ecosystem. 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: • Design and optimise AI-ready tools and APIs that enable LLM platforms (ChatGPT, Claude, Gemini and others) to reliably interact with Canva's design capabilities — focusing on optimising tools to decrease latency and reduce costs without sacrificing end-user performance. Pioneer agent to agent communication. • Build and maintain evaluation frameworks to systematically measure tool-use accuracy across platforms, including proxy-based fast evals for development velocity and real-client evals for production validation. • Experiment with LLM orchestration and agent architectures — Develop Canva agents that any 3rd party provider can call to design quickly, efficiently and at scale. Automate entire workflows such as marketing campaigns by connecting user intent, Canva and third parties. • Develop observability and monitoring systems to track how AI assistants consume Canva's tools in production, identifying failure patterns and driving continuous improvement. • Work across platform boundaries — understanding the behavioural quirks of different LLM platforms and building adapters or configurations that account for them at scale. • Collaborate with AI partners and internal teams to shape tool design, API evolution, and integration strategy aligned with Canva's broader AI ecosystem goals. You're probably a match if • You have experience working with LLMs in production — not just prompt engineering, but rigorous error analysis and understanding how models select and invoke tools, where they fail, and how to improve reliability. • You're skilled in evaluation and benchmarking — you know how to design metrics, build eval pipelines, and measure whether AI integrations are actually working at scale. • You have experience designing APIs or tools consumed by AI agents — understanding that tool descriptions are UX for AI, and small changes in naming or structure can swing accuracy by 40%. • You can build and iterate on agent architectures — whether that's orchestration layers, MCP servers, or intent-based APIs that abstract complexity from external models. • You're proficient in Python and familiar with ML frameworks, but equally comfortable working with TypeScript/Node.js and cloud infrastructure (Cloudflare Workers, AWS, or similar). • You thrive in cross-functional, partner-facing work — collaborating with engineering, product, and external AI platform teams (OpenAI, Anthropic, Google) to shape integration strategy. • You enjoy solving ambiguous, fast-moving problems — the AI ecosystem is evolving rapidly and you're energised rather than overwhelmed by that.