Visual Generation & Multimodal Evaluation Machine Learning Engineer Intern (AML-Ark-US) - 2027 Summer

What you'll do

• Build image and video model and agent evaluations for quality, instruction following, multimodal understanding, and safety.
• Develop automated metrics, model-based evaluators, reproducible human evaluation protocols, and video generation/debugging agents.
• Build large-scale image and video data pipelines and apply evaluation findings to model and product improvements.

What they ask for

• Currently pursuing a Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or a related field.
• Solid foundation in deep learning and computer vision, including generative modeling fundamentals.
• 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 multimodal evaluation framework.

Nice to have

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

Tools

Python, PyTorch, diffusion-based models

AI focus

Evaluation and improvement of visual generation and multimodal models; development of video generation and debugging agents for multi-step creative workflows.