LLM/Multimodal AI Engineer Intern (TikTok Search) - 2027 Start (PhD)

Responsibilities

Our Search Team is responsible for building and owning our search engine which provides our users the best search experience. On the Search Team, you'll have the opportunity to build a full-stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

Responsibilities
- Participate in the development and optimization of algorithms for large-scale search systems under mentor guidance, including query understanding, retrieval, ranking, reranking, and relevance modeling
- Support the application of machine learning, deep learning, and foundation model technologies to improve search relevance, personalization, and user satisfaction
- Explore LLM-powered search technologies in scoped research or engineering modules, such as generative search, retrieval-augmented generation, search agents, long-context understanding, and multi-turn search scenarios
- Contribute to multimodal search capabilities by leveraging text, image, video, audio, user behavior, and other content signals
- Work closely with mentors and cross-functional partners to understand key search quality issues, prototype technical ideas, and contribute to algorithm improvements from research exploration to experimental validation
- Conduct data analysis, model evaluation, and offline/online experiment support to help improve search experience and business impact

Qualifications

Minimum Qualification(s):
- Currently pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Solid programming skills in Python, C++, or a related language
- Good understanding of machine learning and deep learning fundamentals
- Hands-on experience through coursework, lab projects, research projects, internships, or personal exploration in at least one relevant area: search/retrieval, ranking, recommender systems, NLP, multimodal learning, LLMs, or applied ML
- Ability to conduct structured technical exploration, analyze problems, and translate ideas into working prototypes or experimental results under guidance

Preferred Qualification(s):
- Coursework, lab project, competition, open-source, research, or internship experience in search, ranking, NLP, multimodal learning, LLMs, or AI systems
- Technical projects, open-source contributions, competition experience, research exploration, or publications demonstrating interest and capability in relevant domains
- Strong analytical and problem-solving skills, with curiosity and willingness to learn in open-ended, large-scale technical scenarios
- Good communication and collaboration skills, with enthusiasm for learning from mentors and contributing to impactful products
- Passion for applying research ideas and emerging AI technologies to real-world user and business problems

Responsibilities

Responsibilities

Our Search Team is responsible for building and owning our search engine which provides our users the best search experience. On the Search Team, you'll have the opportunity to build a full-stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.
Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts.
Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

Responsibilities
- Participate in the development and optimization of algorithms for large-scale search systems under mentor guidance, including query understanding, retrieval, ranking, reranking, and relevance modeling
- Support the application of machine learning, deep learning, and foundation model technologies to improve search relevance, personalization, and user satisfaction
- Explore LLM-powered search technologies in scoped research or engineering modules, such as generative search, retrieval-augmented generation, search agents, long-context understanding, and multi-turn search scenarios
- Contribute to multimodal search capabilities by leveraging text, image, video, audio, user behavior, and other content signals
- Work closely with mentors and cross-functional partners to understand key search quality issues, prototype technical ideas, and contribute to algorithm improvements from research exploration to experimental validation
- Conduct data analysis, model evaluation, and offline/online experiment support to help improve search experience and business impact

Qualifications

Qualifications

Minimum Qualification(s):
- Currently pursuing a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Solid programming skills in Python, C++, or a related language
- Good understanding of machine learning and deep learning fundamentals
- Hands-on experience through coursework, lab projects, research projects, internships, or personal exploration in at least one relevant area: search/retrieval, ranking, recommender systems, NLP, multimodal learning, LLMs, or applied ML
- Ability to conduct structured technical exploration, analyze problems, and translate ideas into working prototypes or experimental results under guidance

Preferred Qualification(s):
- Coursework, lab project, competition, open-source, research, or internship experience in search, ranking, NLP, multimodal learning, LLMs, or AI systems
- Technical projects, open-source contributions, competition experience, research exploration, or publications demonstrating interest and capability in relevant domains
- Strong analytical and problem-solving skills, with curiosity and willingness to learn in open-ended, large-scale technical scenarios
- Good communication and collaboration skills, with enthusiasm for learning from mentors and contributing to impactful products
- Passion for applying research ideas and emerging AI technologies to real-world user and business problems