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

Responsibilities

Team Introduction
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 our team. As a graduate, 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 date by the end of the year. Please state your availability and graduation date clearly in your resume.

Responsibilities
- Develop and optimize algorithms for large-scale search systems, including query understanding, retrieval, ranking, reranking, and relevance modeling.
- Apply machine learning, deep learning, and foundation model technologies to improve search relevance, personalization, and user satisfaction.
- Explore LLM-powered search technologies, including generative search, retrieval-augmented generation, search agents, long-context understanding, and multi-turn search scenarios.
- Build and improve multimodal search capabilities by leveraging text, image, video, audio, user behavior, and other content signals.
- Collaborate with product, engineering, and research teams to identify key search quality issues, define technical solutions, and drive algorithm improvements from research exploration to production deployment.
- Conduct data analysis, model evaluation, and online/offline experiments to continuously improve search experience and business impact.

Qualifications

Minimum Qualification(s):
- Individuals who are completing or have recently completed a PhD degree 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 in at least one relevant area: search/retrieval, ranking, recommender systems, NLP, multimodal learning, LLMs, or applied ML.
- Ability to conduct structured research or technical problem-solving and translate ideas into working solutions.

Preferred Qualification(s):
- Research, project, or internship experience in search, ranking, NLP, multimodal learning, LLMs, or AI systems.
- Publications, open-source contributions, research projects, or other technical work demonstrating capability in relevant domains (top-tier conference publications are a plus, but not required).
- Strong analytical and problem-solving skills, with a willingness to work on open-ended, large-scale challenges.
- Good communication and collaboration skills, with enthusiasm for building impactful products.
- Passion for applying research to real-world user and business problems.

Responsibilities

Responsibilities

Team Introduction
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 our team. As a graduate, 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 date by the end of the year. Please state your availability and graduation date clearly in your resume.

Responsibilities
- Develop and optimize algorithms for large-scale search systems, including query understanding, retrieval, ranking, reranking, and relevance modeling.
- Apply machine learning, deep learning, and foundation model technologies to improve search relevance, personalization, and user satisfaction.
- Explore LLM-powered search technologies, including generative search, retrieval-augmented generation, search agents, long-context understanding, and multi-turn search scenarios.
- Build and improve multimodal search capabilities by leveraging text, image, video, audio, user behavior, and other content signals.
- Collaborate with product, engineering, and research teams to identify key search quality issues, define technical solutions, and drive algorithm improvements from research exploration to production deployment.
- Conduct data analysis, model evaluation, and online/offline experiments to continuously improve search experience and business impact.

Qualifications

Qualifications

Minimum Qualification(s):
- Individuals who are completing or have recently completed a PhD degree 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 in at least one relevant area: search/retrieval, ranking, recommender systems, NLP, multimodal learning, LLMs, or applied ML.
- Ability to conduct structured research or technical problem-solving and translate ideas into working solutions.

Preferred Qualification(s):
- Research, project, or internship experience in search, ranking, NLP, multimodal learning, LLMs, or AI systems.
- Publications, open-source contributions, research projects, or other technical work demonstrating capability in relevant domains (top-tier conference publications are a plus, but not required).
- Strong analytical and problem-solving skills, with a willingness to work on open-ended, large-scale challenges.
- Good communication and collaboration skills, with enthusiasm for building impactful products.
- Passion for applying research to real-world user and business problems.