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1. Design and iterate on the next-generation video generation foundation architecture.
2. Explore core technologies for long video generation, including long-context attention, KV Cache compression, and memory mechanisms.
3. Research high-compression-ratio video tokenizers and advance unified modeling capabilities for multi-resolution and multi-frame-rate videos.
4. Lead video pre-training at the 10-billion/trillion token scale, defining data mixture and curriculum learning strategies.
5. Explore Scaling Laws, define scientific scale-up paths, and continuously improve key model capabilities.
6. Track industry state-of-the-art , lead comparative experiments, drive technical roadmap decisions, and publish academic papers.
Who We Look For1. Ph.D. in AI-related fields with first-author papers at top-tier conferences.
2. Proficient in the principles and engineering implementation of diffusion models and autoregressive generation.
3. Experience training video/image generation models from scratch; highly proficient in PyTorch and large-scale distributed training.
4. Deep understanding of the design trade-offs in Video VAE/Tokenizers, with 3+ years of relevant research experience.
5. Publications related to video generation or diffusion models.
6. Experience in core industry product R&D or hands-on experience with the latest technologies is preferred.
7. Experience leading end-to-end video foundation model projects is preferred.
Equal Employment Opportunity at TencentAs an equal opportunity employer, we firmly believe that diverse voices fuel our innovation and allow us to better serve our users and the community. We foster an environment where every employee of Tencent feels supported and inspired to achieve individual and common goals.