About the team
The Seed LLM Post Training team is responsible for researching cutting-edge posttrain technologies and providing core posttrain capabilities for unified multimodal large models. The team's goal is to research and explore next-generation advanced technologies such as SFT, RM, RL, and self-learning during the posttrain phase, while significantly optimizing and improving key areas including reasoning, coding, agent, and omni model.
Responsibilities
- Explore large-scale models and optimize systems.
- Data construction, instruction tuning, preference alignment, and model optimization.
- Improving relevant model capabilities, such as reasoning, code, math etc.
- In-depth research and exploration of future use cases.Minimum Qualifications:
- Currently pursuing a PhD in Computer Science, AI, or a related field.
- Research experience in reinforcement learning, sequential decision-making, or agent behavior.
- First-author publications in accredited ML/AI conferences (e.g., NeurIPS, ICLR, ICML).
- Solid programming and experimentation skills, including with RL or LLM frameworks.
Preferred Qualifications:
- Experience with LLM agents, tool use, or prompt-based control.
- Familiarity with environments such as WebArena, ALFWorld, or programmatic reasoning tasks.
- Understanding of RL techniques such as reward shaping, memory augmentation, or curriculum learning.
As a condition of employment, all successful candidates must be able to establish authorization to work in the United States. For this position, the Company does not provide sponsorship or any immigration-related benefits.