Research Scientist Intern – TikTok Search / Generative AI (LLM) - Global Frontier Tech Recruitm[...]

TikTok; San Jose (CA); On-site; USD 68,191 - 97,120; Full time

Benefits offered by this job

Health insurance

Paid holidays

Housing allowance

Job summary

TikTok is seeking a Campus Intern for its Search team in San Jose, CA, focused on developing AI-driven search systems. The role involves supporting large model integration, improving personalization, and contributing to multimodal search capabilities. Ideal candidates are pursuing a PhD in fields like Computer Science, with a solid understanding of machine learning and proficiency in Python. Intern benefits include health insurance, paid holidays, and potential housing allowance. Apply if you are ready for a challenging position in a fast-paced environment.

Qualifications

• Currently pursuing a PhD in a relevant field.
• Solid foundation in machine learning or deep learning.
• Familiarity with LLMs, NLP, or multimodal learning.
• Proficient in Python with ML frameworks experience.
• Strong problem-solving skills and willingness to learn.

Responsibilities

• Support the development of AI search systems using large models.
• Assist in improving ranking and personalization in search.
• Contribute to generative and multimodal search models.
• Explore LLM-based approaches for complex queries.
• Help optimize retrieval and ranking performance.
• Collaborate with mentors and cross-functional teams.

Skills

Machine learning

Deep learning

Information retrieval

Python

Problem-solving

Education

PhD in Computer Science, Machine Learning, or related fields

Tools

PyTorch

TensorFlow

Job description

About the Team

The TikTok Search team is responsible for delivering a world-class search experience across TikTok’s global ecosystem. Our mission is to connect users with the most relevant and high-quality content through advanced technologies in search ranking, recommendation, and multimodal understanding. As a campus hire, you will collaborate with top engineers and researchers to solve challenging problems at scale, working across the full stack of search—from content understanding and retrieval to ranking and user experience optimization.

Project Overview, Challenges & Value

With the rapid evolution of pre-trained large models, TikTok Search is advancing toward a new paradigm of AI-native search. Traditional search systems face increasing limitations when handling massive-scale data, multimodal content (video, text, image), and complex user intents. This project focuses on building a next-generation generative search system powered by large models to significantly enhance search intelligence and user experience.

Key Focus Areas

• Integrating large models with ranking systems to improve personalization and relevance.
• Developing end-to-end generative search models based on multimodal pretraining.
• Exploring large model–driven agent frameworks to better support complex, ambiguous, and multi-turn search scenarios.

Key Challenges

• Personalized ranking: Fully leveraging multimodal signals beyond traditional model capacity.
• Ultra-large-scale retrieval and ranking: Scaling search systems to efficiently handle hundreds of billions of candidates.
• Complex query understanding: Accurately interpreting long, ambiguous, and multi-turn queries to improve user satisfaction.

Project Value

• Technical Value: Drive innovation in large model–powered search architecture and enable agent-based AI search systems.
• Business Value: Significantly improve search relevance and user satisfaction, strengthening TikTok’s search engagement and long‐term growth.

Opportunity

We are looking for talented individuals to join our team in 2027. As an intern, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding during the summer 2027. Please state your availability clearly in your resume.

Responsibilities

• Support the development of AI search systems using large models (LLMs).
• Assist in improving ranking, personalization, and relevance in search.
• Contribute to generative and multimodal search models (video, text, image).
• Explore LLM-based approaches for complex and multi-turn queries.
• Help optimize retrieval and ranking performance at scale.
• Collaborate with mentors and cross‑functional teams to prototype and evaluate solutions.

Qualifications

Minimum Qualifications

• Currently pursuing a PhD in Computer Science, Machine Learning, Artificial Intelligence, or related fields.
• Solid foundation in machine learning, deep learning, or information retrieval.
• Familiarity with at least one of the following: LLMs, NLP, search/recommendation, or multimodal learning.
• Proficiency in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow).
• Strong problem‑solving skills and willingness to learn in a fast‑paced environment.

Preferred Qualifications

• Research experience demonstrated through projects, publications, or open-source contributions.
• Experience with large-scale data, model training, or system implementation.
• Exposure to search, recommendation, or ads systems.
• Experience with multimodal models or generative AI applications.
• Interest in LLMs, agent-based systems, or end-to-end AI applications.

Job Information

【For Pay Transparency】Compensation Description (Hourly) – Campus Intern. The hourly rate range for this position in the selected city is $60‑$60.

Benefits

Benefits may vary depending on the nature of employment and the country work location. Interns have day one access to health insurance, life insurance, wellbeing benefits and more. Interns also receive 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Interns who are not working 100% remote may also be eligible for housing allowance.

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

Los Angeles County Fair Chance Statement

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; and
• Exercising sound judgment.

Accommodation Statement

TikTok 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 https://tinyurl.com/RA-request.