Fundamental Research Scientist

At Canva, we're building a future powered by AI that's as magical as it is impactful. As a Research Scientist at Canva, you'll be responsible for advancing the future of AI by experimenting with cutting-edge techniques, as well as improving models for real-world quality and performance.

About the role:

You will be able to reshape the landscape of frontier AI research directions by pre-training/post-training frontier multi-modal generation models with high-end GPUs on large, high-quality datasets. You will be able to coordinate with talented individuals with deep domain expertise and great passion. You will have the opportunity to redefine how AI revolutionizes productivity softwares by bringing the best AI models to hundreds of millions of active users.

At the moment, this role is focused on:

• Research Direction: Determining and leading research initiatives aligned with the tend of frontier multimodal AI research and product goals

• Research and Experimentation: Designing and running experiments to validate hypotheses on the high-end GPUs

• Analysis: Interpreting experimental results and translating them into actionable insights

• Model Innovation: Creating novel generative model architectures, training methodologies, RL algorithms, novel synthetic data generation pipeline.

You’re probably a match if you have:

• Rich experience in the development, training, and iteration of foundational large-scale text-to-image/video/3D generation models (diffusion models or auto-regressive models) based on both internal research and external advancements, such as emerging trends, technologies, and open challenges

• Strong academic and professional track record, including peer-reviewed publications in top-tier conferences like CVPR/ICCV/ECCV/NeurIPS/ICML/ICLR and open-source contributions

• Rich experience in large-scale parallel model pre-training across hundreds of GPUs

• Proficiency in Python, PyTorch, Diffusers, Transformers, Megatron, DeepSpeed, and cloud computing platforms, ensuring efficient model training and deployment

• Ability to share your knowledge internally through documentation and cross-team collaborations, and externally through research papers or talks where appropriate

• Curiosity! Always looking to stay ahead of industry trends by tracking AI literature, competitors, and emerging technologies