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

What you'll do

• Build image and video model/agent evaluation systems, metrics, and reproducible human evaluation protocols.
• Develop agents for video generation and debugging that orchestrate 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

• 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 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 through publications, substantial projects, internships, or open-source work.

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 image and video generation, multimodal understanding, instruction following, and safety; develops video-generation and debugging agents and supports model improvement.