Student Researcher (LLM Post Training – Agent & Reinforcement Learning) - 2026 Start (PhD)

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.

Requirements:

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 Web Arena, 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.