Staff Machine Learning Engineer - Recommendations (AI)

TL;DR

Staff Machine Learning Engineer - Recommendations (AI): Design, implement, and refine production recommendation systems that personalize Canva experiences with an accent on large-scale ML engineering, applied research integration, and online/offline experimentation. Focus on improving model architecture and performance, validating recommender quality with rigorous evaluation, and shaping how recommendation models integrate reliably across the broader technology stack.

Location: Remote-friendly within Australia (Sydney campus; flexibility to work from home or a mix of spaces)

Company

Canva builds AI-powered design experiences and personalized recommendations for millions of users.

What you will do

• Design, implement, and refine machine learning models for personalized recommendations, focusing on the most complex and ambiguous parts of the system.
• Improve ML system architecture, code structure, and performance to raise engineering quality across the team.
• Evaluate state-of-the-art research and decide what to bring into production.
• Lead online and offline experiments to validate model performance and make data-driven shipping/iteration decisions.
• Ensure strong performance and reliability by shaping how ML models integrate with the broader technology stack.
• Collaborate with product and engineering teams to deploy recommendation features; mentor MLEs and communicate results to technical and non-technical stakeholders.

Requirements

• Must be able to work within Australia (remote-friendly within Australia).
• Significant experience developing, shipping, and operating production-scale recommendation systems.
• Strong ML engineering skills with Python and core ML tooling (PyTorch, pandas, scikit-learn, numpy), including training pipelines, evaluation, and serving.
• Proven ability to rigorously evaluate model performance and make data-driven decisions.
• Excellent communication skills, including explaining complex technical concepts to senior leadership.
• Collaborative mindset working cross-functionally with engineers, data scientists, and product managers.

Culture & Benefits

• Remote-friendly setup within Australia, with flexibility to work from home or a mix of co-working spaces.
• Equity packages.
• Inclusive parental leave policy.
• Annual Vibe & Thrive allowance for wellbeing, social connection, and office setup.
• Flexible leave options to recharge.
• All interviews conducted virtually.

Hiring process

• Virtual interviews to evaluate experience, skills, and fit.
• Discussion of reasonable adjustments during the interview process if needed.