Research Scientist - TikTok E-Commerce Recommendation Foundation

Research Scientist - Tik Tok E-Commerce Recommendation Foundation

Location:

San Jose

Employment Type:

Regular

Job Code: A173183A

The base salary range for this position in San Jose is $156,000 - $387,600 annually.

• Build and optimize cross-scenario shared Foundation Models to enable unified modeling and efficient inference.
• Advance the event-sequence-driven generative recommendation paradigm, integrating multimodal understanding and generative capabilities.
• Apply LLM technologies across retrieval, ranking, and re-ranking stages; participate in model training, inference optimization, and system co-design.
• Explore the integration of LLMs / VLMs with recommendation systems to develop adaptive and evolving intelligent recommenders.
• Research end-to-end generative recommendation and system optimization methods that balance efficiency and user experience.

• MS/PhD in Computer Science, related technical field or equivalent industrial research experience.
• Solid theoretical foundation in machine learning, deep learning, or information retrieval.
• Proficiency in Python and familiarity with mainstream deep learning frameworks (e.g., PyTorch).
• Strong passion for intelligent recommendation systems and a self-driven research mindset.

• Experience in large-scale recommendation system development or large-model training, with notable technical achievements in a sub-area.
• Research experience or publications in LLMs, multimodal learning, reinforcement learning, or generative recommendation.
• Familiarity with pre-training and post-training processes for large language models (LLMs) or Foundation Models.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

• Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues.
• Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems.
• Exercising sound judgment.