Research Scientist Graduate (TikTok Recommendation-Agentic AI) - 2026 Start (PhD)

Responsibilities

• Design and construct reinforcement learning datasets tailored for recommendation scenarios.
• Explore and optimize reinforcement learning algorithms, and develop scalable training and inference frameworks.
• Conduct research on agentic recommendation systems and generative recommendation models.
• Stay up to date to the latest SoTA advancements in relevant areas, and translate research ideas into real-world applications.

Requirements

• Successful candidates must be able to commit to an onboarding date by end of year 2026
• We will prioritize candidates who are able to commit to these start dates.
• Please state your availability and graduation date clearly in your resume.
• Final-year Ph.D. candidate or recent Ph.D. graduate in Computer Science or a related field.
• Strong knowledge and hands-on experience in at least one of the following areas: reinforcement learning, agent development, or LLM post-training.
• Passion for exploring cutting-edge research topics and bridging theory with practice.

Preferred

• Publications in accredited academia conferences such as NeurIPS, ICML, ICLR, AAAI, IJCAI, RecSys, KDD, WWW, or WSDM.
• Internship or project experience related to reinforcement learning, agent-based systems, or LLM alignment/post-training.

Hiring process

Applications will be reviewed on a rolling basis. We encourage you to apply early.