AI Machine Learning Engineer Graduate - TikTok Search

Responsibilities

Team Introduction Our Search Team is responsible for building and owning TikTok's search engine which provides our users the best search experience. On the TikTok 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 in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company. Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities - Exploring Cutting-Edge NLP Technologies: From basic tasks like word segmentation and Named Entity Recognition (NER) to advanced business functions like text and multimodal pre-training, query analysis, and fundamental relevance modeling, we apply deep learning models throughout the pipeline where every detail presents a challenge. - Cross-Modal Matching Technologies: Applying deep learning techniques that combine Computer Vision (CV) and Natural Language Processing (NLP) in search, we aim to achieve powerful semantic understanding and retrieval capabilities for multimodal video search. - Large-Scale Streaming Machine Learning Technologies: Utilising large-scale machine learning to address recommendation challenges in search, making the search more personalized and intuitive in understanding user needs. - Architecture for data at the scale of hundreds of billions: Conducting in-depth research and innovation in all aspects, from large-scale offline computing and performance and scheduling optimization of distributed systems to building high-availability, high-throughput, and low-latency online services. - Recommendation Technologies: Leveraging ultra-large-scale machine learning to build industry-leading search recommendation systems and continuously explore and innovate in search recommendation technologies.

Qualifications

Minimum Qualifications: - Final year Ph.D or recent Ph.D graduates in Computer Science, engineering or quantitative field. - Proficient coding skills and strong algorithm & data structure using C++/Python/Java. - Have a solid knowledge of machine learning and practical experience in applying it. Preferred Qualifications: - Effective communication and teamwork skills. - Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV. - Have a solid foundation in algorithms related to LLMs, including but not limited to comprehensive learning and practical experience in areas such as single-modal/multi-modal LLM application and deployment. - Strong publications record in top conferences or journals（e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, NAACL, CVPR, ICCV and ECCV）. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://jobs.bytedance.com/en/legal/privacy If you have any questions, please reach out to us at [email protected]

Job Information