Job Description

Job Description
1. Engage in the R&D of large-scale video world models, including the design and construction of training datasets, foundational model architecture design,optimization of pre-training/SFT/RL pipelines, model capability evaluation, and exploration of diverse downstream application scenarios.

2. Conduct scientific analysis of R&D challenges, identify performance bottlenecks,and derive solutions from first principles to accelerate the development and iteration of world models, ensuring competitive edge and technical leadership.

3. Explore alternative paradigms for implementing world models, investigate next-generation model architectures, and push the boundaries of what world models can achieve.

Skills Required
1. Bachelor's degree or higher (preferred) in Computer Science, Artificial Intelligence, Mathematics, or related fields (full-time education required).

2. Solid foundation in deep learning algorithms and proven hands-on experience in large model R&D. Experience with Diffusion Models and Autoregressive Modelsis highly preferred. Publications in top-tier conferences/journals and practical experience in text-to-image/video generation are strong pluses.

3. Proficient in the underlying implementation details of various deep learning networks and operators experienced in training/inference optimization, CPU/GPU acceleration, and distributed training/inference acceleration. Practical experience is highly valued.

4. Exceptional candidates with ACM-ICPC or NOIP competition experience will begiven top priority.

5. Strong learning agility, effective communication skills, teamwork spirit, and akeen sense of curiosity.