AI Engineer Graduate - LLM/Multimodal

Responsibilities

Team Introduction TikTok 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. - AI Search & AI Bot Team: Specializes in LLM application algorithm R&D for TikTok Search, covering core scenarios including AI Search Q&A cards and TikTok's official AI Assistant. We leverage LLM ChatBot, Agent, and RAG technologies to deliver accurate, real-time search responses for users, driving business growth through deep integration of technical innovation and business scenarios. - Multimodal Large Model Team: Builds industry-leading large model-based search technology, with deep expertise in NLP, CV, and multimodal technology domains. We explore cutting-edge technology applications in complex search scenarios, with technical achievements directly empowering TikTok Search functions to enhance user experience. - Local Services Search Team: Optimizes Local Service search experience, helping users discover catering, hotel, leisure and other life services. We apply LLM for query understanding, CTR/CVR prediction, local-service ai search card and agentic local service search framework. - Vertical Search Team: Build a full-stack search engine serving billions of global users, covering vertical scenarios such as photo-text search, user search, live search and music search. The scope also encompasses AI-powered search for standalone apps including Drama and Lemon8. We leverage LLM, NLP, and multimodal understanding technologies to iteratively enhance search quality and system performance. - Search Ranking Team: By building a full stack search engine system based on advanced AI and machine learning models, we provide industry-leading search experience for billions of global users. We have cutting edge technologies in fields like LLM for Recommendation, Large Ranking Model, Sequence Modeling, Multi-modal Understanding, etc. 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. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Build AI Search Agents with planning, memory, and tool-use capabilities, applying reinforcement learning, knowledge representation, and automated decision-making technologies to solve complex problems end-to-end. - Optimize LLM-based query understanding capabilities, process multi-turn conversation semantic analysis, and ensure accurate and objective search results through LLM reasoning. - Develop LLM technologies to adapt to diverse search scenarios, including pre-training strategies and efficient RLHF algorithms, to improve core metrics such as search relevance and timeliness. - Utilize multimodal large models for visual representation learning and video understanding, strengthening search retrieval capabilities. - Optimize RAG and LLM pipelines, improve retrieval ranking algorithms, train and optimize LLM answer generation capabilities (e.g. fine-tuning, inference optimization), and enhance the relevance and structured presentation of search results. - Translate cutting-edge LLM/Agent technology research outcomes into production environments, collaborating with cross-functional teams to drive product iteration and upgrades.

Qualifications

Minimum Qualifications: - Individuals who have minimally completed a Bachelor's degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline. - Proficient in C++/Python, with solid foundation in algorithms and data structures. - Basic understanding of LLM fundamental principles (e.g. prompt engineering, fine-tuning workflows). - Strong problem-solving skills with proven experience delivering technical projects. - Solid foundation in machine learning and deep learning, with practical experience in NLP, CV or related domains. - Excellent analytical and problem-solving abilities. Preferred Qualifications: - Hands-on experience with LLM/Agent related technologies: RAG optimization, LLM RLHF/SFT, Agent framework development (e.g. planning/memory modules). - Relevant experience in search, recommendation or advertising domains. - Publication experience in top conferences (ICLR, NeurIPS, ICML, ACL, CVPR, etc.) is a plus. - Excellent communication and collaboration skills, with a passion for exploring new technologies and driving technical implementation.

Job Information