Design and implement workload scheduling across multiple data centers, regions, and cloud environments, ensuring balanced resource utilization and efficient placement of both online services and offline batch jobs.
Design and execute persona/role-playing evaluation frameworks, covering metrics such as identity recognition, role compatibility, multi-turn stability, and style consistency.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Design and execute persona/role-playing evaluation frameworks, covering metrics such as identity recognition, role compatibility, multi-turn stability, and style consistency.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.
Design and execute persona/role-playing evaluation frameworks, covering metrics such as identity recognition, role compatibility, multi-turn stability, and style consistency.
Synthetic Data Methodology : Design physics-constrained generative model approaches (diffusion models, VAEs) for synthetic data generation. Deliver validated methodology and training recipes for pipeline operationalization.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.