You will lead and grow a team of high-performing Machine Learning Engineers and Research Scientists (EU based) who are advancing the future of AI at scale.
Your focus will be on setting strategic technical direction, coaching others to deliver impactful engineering solutions, and ensuring the deployment of robust, scalable ML systems into production.
You'll champion both engineering excellence and measurable impact, bridging foundational model capabilities with real-world deployment across Canva's platform.
Coaching and mentoring a high-performing team of Machine Learning Engineers and Research Scientists.
Owning the evaluation infrastructure
Design, build, and maintain robust evaluation systems, quality metrics, safety monitoring, red-teaming, competitive benchmarking
to guarantee enterprise readiness and user delight at scale.
Building automated metrics that reliably predict human aesthetic judgment across dimensions like visual hierarchy, layout coherence, typography, and brand alignment.
Advising on human evaluation pipelines and closing the loop between user signals and model improvements.
Setting technical strategy in alignment with Canva's AI and product goals.
Guiding engineering direction across model deployment, evaluation infrastructure, and production systems.
Partnering cross-functionally to ensure ML capabilities translate into reliable product impact.

Have led machine learning engineering teams, with a strong track record of coaching and delivering production systems.
Possess expert knowledge in deploying and scaling generative models (Diffusion, GANs, VAEs, LLMs) in production environments with a strong focus on visual models (image, video, design).
Bring 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.
Have experience with visual quality assessment, aesthetic modelling, or human preference learning – bonus if you've tackled the gap between automated metrics and human raters.
Understand design principles (hierarchy, balance, typography, colour theory) well enough to operationalise them as measurable signals.
Thrive in collaborative environments and communicate clearly with technical and non-technical audiences.
Stay current with both SOTA research trends and engineering best practices, energised by continuous learning.

Equity packages
we want our success to be yours too
Inclusive parental leave policy that supports all parents & carers
An annual Vibe & Thrive allowance to support your wellbeing, social connection, home office setup & more
Flexible leave options that empower you to be a force for good, take time to recharge and supports you personally

Machine Learning Engineering Manager – Evaluations

Key skills