Fundamental Research Scientist
Job Description
Company Description
该岗位现面向所有经验阶段的候选人开放，包括社会招聘、2025年及2026年应届毕业生，同时开放实习生岗位。工作地点为北京。欢迎申请，期待你的加入！
Notice: This position is open to candidates at all experience levels, including experienced candidates, 2025 and 2026 graduates, as well as internship opportunities. The role is based in Beijing. We welcome your application and look forward to having you on board!
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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.
Job Description
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 software like social media, Word, and PowerPoint 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.
Qualifications
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
