Global Frontier Tech Recruitment Program - Intern

Ellis Technologies, Inc.; San Jose (CA); On-site; USD 68,191 - 97,120; Part time

Benefits offered by this job

Health Insurance

Paid Holidays

Wellbeing Benefits

Job summary

Ellis Technologies, Inc. is seeking a Research Scientist Intern for the TikTok Search team in San Jose, California. The internship offers hands-on experience in developing large model-based search systems and improving AI search capabilities.

Ideal candidates are pursuing a PhD in Computer Science or related fields and have a strong foundation in machine learning and Python. Interns will collaborate with experts and receive benefits including health insurance and paid holidays.

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.

Responsibilities

• Support the development of AI search systems using large models (LLMs).
• Assist in improving ranking, personalization, and relevance in search.
• Collaborate with mentors and cross-functional teams to prototype and evaluate solutions.

Skills

Machine Learning

Deep Learning

Information Retrieval

Python

Large Models (LLMs)

NLP

Education

Pursuing a PhD in Computer Science or related fields

Tools

PyTorch

TensorFlow

Job description

Research Scientist Intern – TikTok Search / Generative AI (LLM) - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Location: San Jose

Employment Type: Intern

Job Code: A29723

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.

We are looking for talented individuals to join us for an internship in 2026. PhD internships at our Company provide students the opportunity to actively contribute to products and research, and to the organization’s future plans and emerging technologies. Our dynamic internship experience blends hands‑on learning, enriching community‑building and development events, and collaboration with industry experts.

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.

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.
• Previous internship or research experience in industry or labs.

Job Information

The hourly rate range for this position in the selected city is $60- $60.

Benefits

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.

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:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.