Research and development of large-scale video world models, including design, training, optimization, evaluation, and application exploration, to maintain competitiveness and leadership in the field.
Requirements
- Solid foundation in deep learning algorithms and proven experience in large model R&D.
- Candidates with experience in Diffusion Models and Autoregressive Models, publications in top-tier conferences, or practical experience in text-to-image/text-to-video generation are preferred.
- Familiarity with implementation details of deep learning networks and operators, model tuning for training/inference, CPU/GPU acceleration, and distributed training/inference optimization.
- Hands-on experience is a plus.
Responsibilities
- Engage in the research and development of large-scale video world models, including the design and construction of training datasets, foundational model algorithm design, optimization related to pre-training, SFT, and RL, model capability evaluation, and exploration of downstream application scenarios.
- Analyze R&D challenges scientifically, identify performance bottlenecks, and develop solutions based on first principles to accelerate the development and iteration of world models, ensuring competitiveness and leadership.
- Explore diverse paradigms for world model implementation, research next-generation model architectures, and push the boundaries of world model capabilities.
Other
- Bachelor’s degree or higher (preferred) in Computer Science, Artificial Intelligence, Mathematics, or a related field.
- Participation in ACM/NOIP competitions is highly desirable.
- Strong learning, communication, and teamwork skills, coupled with a keen sense of curiosity.
- The expected base pay range for this position in the location(s) listed above is $80,169.00 to $120,000.14 per year.
- This position will be eligible for 1 hour of paid sick leave for every 30 hours worked and up to 13 paid holidays throughout the calendar year.
