Staff Machine Learning Engineer (Recommendations)

TL;DR

Staff Machine Learning Engineer (Recommendations): Designing and implementing production-scale ML models to personalize content discovery for millions of users with an accent on recommendation algorithms and system architecture. Focus on integrating state-of-the-art research into production, optimizing high-traffic ML pipelines, and leading large-scale experiments to improve user engagement.

Location: Must be based in Australia (Remote-friendly within the country)

Company

Canva is a global design platform redefining how the world experiences design.

What you will do

• Design and refine complex ML models for personalized recommendations including templates, images, and fonts.
• Improve the architecture, code structure, and performance of high-traffic machine learning systems.
• Investigate and implement state-of-the-art ML models from recent research papers.
• Lead the design of online and offline experiments to validate model performance and drive shipping decisions.
• Collaborate with product and engineering teams to deploy new recommendation features across the technology stack.
• Mentor other MLEs through reviews and pairing, and communicate technical direction to senior leadership.

Requirements

• Significant experience developing and operating production-scale recommendation systems.
• Proficiency in Python and core ML tooling such as PyTorch, pandas, scikit-learn, and numpy.
• Strong fluency in ML engineering, including training pipelines, evaluation, and serving.
• Track record of rigorously evaluating model performance and making data-driven decisions.
• Excellent communication skills to explain complex technical concepts to diverse audiences.
• Must be based in Australia.

Culture & Benefits

• Equity packages to share in the company's success.
• Inclusive parental leave policy supporting all parents and carers.
• Annual Vibe & Thrive allowance for wellbeing, social connection, and office setup.
• Flexible leave options to recharge and support personal needs.
• High degree of flexibility in work arrangement (home, office, or hybrid) within Australia.

Hiring process

• All interviews are conducted virtually.