Visual Generation & Multimodal Evaluation Researcher Graduate (AML-Ark-US) - 2027 Start (PhD)

What you'll do

• Build evaluation systems and metrics for image and video models and agents, including human evaluation protocols.
• Develop video-generation and debugging agents for multi-step creative workflows.
• Build large-scale image and video data pipelines and apply evaluation findings to model and product improvements.

What they ask for

• Completing or recently completed a PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a related field.
• Strong foundation in deep learning, computer vision, and generative modeling.
• Practical experience in at least one of visual generation, multimodal LLMs, video understanding, or visual quality assessment.
• Strong Python skills and proficiency with PyTorch or an equivalent framework, or a multimodal evaluation framework; demonstrated research or engineering ability.

Nice to have

• Publications at top-tier vision or ML venues, such as NeurIPS, ICML, CVPR, ICCV, or ECCV.
• Experience with diffusion-based models and post-training, visual generation benchmarks or evaluation frameworks, agent frameworks for creative workflows, or large-scale video data infrastructure.

Tools

Python, PyTorch

AI focus

Evaluates and improves image and video generation models and agents; develops multimodal evaluation methods and agents for creative workflows.