Senior Machine Learning Engineer - Visual Suite - Productivity Group (ANZ remote)

📋 Description

• • Shape the future of productivity at Canva by owning the machine-learning backbone of the Visual Suite—our rapidly growing collection of Docs, Email, Sheets, Presentations, Websites, and Whiteboards that already serve millions of users across ANZ and beyond.
• • Act as the technical anchor for a cross-functional squad of backend and ML engineers, product managers, and designers, translating ambitious product visions into scalable, production-grade ML services that run 24/7 on AWS and GCP.
• • Debug, profile, and optimise inference pipelines that power real-time features such as auto-layout, content generation, image upscaling, and semantic search—reducing P99 latency by double-digit percentages while keeping cloud costs flat.
• • Build reusable ML “blueprints” (feature stores, model registries, serving templates, monitoring dashboards) that allow squads across Design Experience to ship new AI capabilities in days instead of weeks.
• • Partner directly with product teams to co-design experiments, define success metrics, and ship A/B tests that validate model improvements and user delight, iterating at the pace of a weekly release train.
• • Champion MLOps best practices—CI/CD for models, automated retraining, canary rollouts, and drift detection—so every experiment you ship is safe, observable, and reversible.
• • Influence the technical roadmap by surfacing pain points, proposing architectural bets, and securing buy-in from senior leadership; your proposals regularly become OKRs for the entire Productivity Group.
• • Mentor mid-level and junior ML engineers through pair programming, design reviews, and lightning talks, turning high-potential talent into high-impact contributors.
• • Contribute to Canva’s open-source ML tooling and blog posts, sharing battle-tested patterns with the global community and reinforcing our reputation as an AI-first product company.
• • Stay ahead of the curve—evaluating cutting-edge research in vision transformers, diffusion models, and multimodal embeddings—then distilling the hype into pragmatic solutions that ship to production within one quarter.
• • Balance rapid experimentation with long-term platform health: refactor legacy code paths, eliminate tech debt, and ensure every service you touch is faster, cheaper, and more reliable than before.
• • Enjoy the freedom of remote-first work across Australia or New Zealand while still tapping into vibrant campus culture through quarterly on-site hackathons and team summits in Sydney or Melbourne.
• • Thrive in a high-velocity environment where priorities can pivot overnight; you see ambiguity as an opportunity to lead, not a blocker to wait out.
• • Celebrate wins big and small—from a 1 % lift in user engagement to a 50 % reduction in infra spend—knowing each improvement compounds into a product that democratises design for the planet.