Student Researcher Seed - Multimodal Interaction & Model - RL Focused PhD

Position: Student Researcher [Seed - Multimodal Interaction & World Model - RL Focused] - 2026 Start (PhD)
The Seed Multimodal Interaction and World Model team is dedicated to developing models that boast human-level multimodal understanding and interaction capabilities. The team also aspires to advance the exploration and development of multimodal assistant products.

- Design and implement reinforcement learning (RL) training systems for large-scale multimodal foundation models - Develop unified modeling frameworks that integrate video, audio, and language, with a focus on visual latent reasoning - Explore RL-based approaches to bridge understanding and generation for multimodal visual reasoning - Collaborate with researchers to evaluate models on tasks involving world modeling, reasoning, and instruction-conditioned generation

Minimum Qualifications:

- Currently pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline - Publications in top-tier venues, such as CVPR, ECCV, ICCV, NeurIPS, ICLR, ICML, or other leading conferences in AI and ML - Strong research background in at least one of the following: reinforcement learning, multimodal learning, video understanding, or vision-language modeling - Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

- Experience with reinforcement learning in multimodal or interactive environments - Familiarity with video generation or diffusion-based generative models

- Experience with large-scale model training (e.g., distributed training, curriculum learning, or memory-augmented transformers) - Solid programming and engineering skills, with experience building training or evaluation pipelines for ML models