Machine Learning Engineering Manager, Evaluations

• Lead and grow a team of high-performing Machine Learning Engineers and Research Scientists advancing the future of AI at scale. • Own the evaluation infrastructure designing, building, and maintaining robust evaluation systems, quality metrics, safety monitoring, and competitive benchmarking. • Bridge rigorous engineering with practical application turning cutting-edge ML capabilities into delightful product experiences.

• Have led machine learning engineering teams with a strong track record of coaching and delivering production systems. • Have expert knowledge in deploying and scaling generative models such as Diffusion, GANs, VAEs, and LLMs in production environments with a strong focus on visual models. • Have hands-on experience building ML infrastructure, evaluation pipelines, and monitoring systems at scale. • Excel at creating data-driven evaluation methodologies turning user analytics and production metrics into clear actionable insights. • Have strong systems design skills and experience with MLOps, model serving, and production reliability. • Thrive in collaborative environments and communicate clearly with technical and non-technical audiences. • Stay current with both SOTA research trends and engineering best practices.

• Have experience with visual quality assessment, aesthetic modelling, or human preference learning. • Have tackled the gap between automated metrics and human raters. • Understand design principles such as hierarchy, balance, typography, and colour theory well enough to operationalise them as measurable signals. • Have experience building automated metrics that predict human aesthetic judgement.

• Coach and mentor a high-performing team of Machine Learning Engineers and Research Scientists. • Design, build, and maintain robust evaluation systems, quality metrics, safety monitoring, red-teaming, and competitive benchmarking to guarantee enterprise readiness and user delight at scale. • Build automated metrics that reliably predict human aesthetic judgement across dimensions like visual hierarchy, layout coherence, typography, and brand alignment. • Advise on human evaluation pipelines and close the loop between user signals and model improvements. • Set technical strategy in alignment with Canva AI and product goals. • Guide engineering direction across model deployment, evaluation infrastructure, and production systems. • Partner cross-functionally to ensure ML capabilities translate into reliable product impact.

• Receive equity packages. • Access inclusive parental leave policy that supports all parents and carers. • Receive an annual Vibe and Thrive allowance to support wellbeing, social connection, and home office setup. • Access flexible leave options that empower you to be a force for good and take time to recharge. • Work from the London campus in Hoxton Square Shoreditch with choice in where and how you work.

Canva is redefining how the world experiences design. As Canva grows, so does the impact and opportunity of AI-powered features. The company follows a hybrid way of working from its London campus trusting team members to choose the balance that empowers them and their team to achieve their goals.