Research Scientist - TikTok E-Commerce Recommendation Foundation Job Seattle area,Washington USA,IT/Tech

Research Scientist - Tik Tok E-Commerce Recommendation Foundation

Location:

Seattle

Employment Type:

Regular

Job Code: A222038A

Salary range: $148,200 - $300,960 annually.

Benefits:
Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

Team

The E-commerce Recommendation Foundation team is dedicated to building the next-generation recommendation intelligence. We aim to develop a unified Foundation Model that supports multi-business and multi-scenario recommendation systems, covering the full pipeline from retrieval and ranking to re-ranking, and driving a comprehensive upgrade in intelligence and generative capability. We believe the future of recommendation systems goes beyond predicting click-through rates — it lies in understanding the relationship between people and content, and in generating new connections.

The team is exploring an event-sequence-driven generative recommendation paradigm, deeply integrating large language models (LLMs), multimodal understanding, reinforcement learning, and system optimization to advance recommendation systems toward general-purpose intelligent agents. We value original exploration and encourage both research thinking and engineering excellence. Every team member is empowered to propose hypotheses and validate ideas in an open environment — your code and papers may help define the next paradigm of recommendation systems.

We seek individuals with a general intelligence mindset to join us in redefining the future of recommendation.

Responsibilities

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.

Qualifications

Minimum Qualifications

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.

Preferred Qualifications

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.

Legal Notice

For Los Angeles County (unincorporated) Candidates:
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.

Accommodation

Tik Tok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at

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