Video Generation Content Understanding and Feedback Researcher
Core
Researching model capabilities to understand generated video content, including semantics, objects, relationships, and spatial structures, while implementing state tracking and consistency modeling for real-time interactive generation pipelines.
Role type
Researcher (Video Generation Content Understanding and Feedback)
Builds
Proprietary technical roadmaps and evaluation systems for controllable interactive video generation in game scenarios.
Domain
AI Research, Video Generation, Game AI
Deliverable
production ML models
Required skills
Video understanding, Video prediction, Reinforcement learning, Multimodal generation and understanding, Diffusion model principles, Model training pipeline design, Python, PyTorch
Preferred skills
Game AI, Simulation environments, Closed-loop systems, Publications in top-tier conferences
Technologies
PyTorch, Diffusion models
Responsibilities
Research model ability to parse semantics and spatial structures in generated content, Implement state tracking and consistency modeling, Explore unified generation-understanding architectures, Research causal consistency control and physical constraints, Collaborate with Agent/RL teams for end-to-end closed loops, Validate controllable interactive capabilities in game scenarios, Track industry work and formulate technical roadmaps
Seniority
Senior, hands-on IC