Machine Learning Research Scientist Graduate (Business Integrity) - 2026 Start (PhD)

Team Introduction

Our Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users’ needs with reliable and high-performing platforms and services. We are looking for strong machine learning engineers who are excited to grow their business understanding, build highly scalable machine learning models, and partner across disciplines with global teams, in pursuit of excellence. Given the fast growth of TikTok in the world, we are working on building a next-generation content understanding system for TikTok monetization. We are seeking machine learning engineers at all levels experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value. 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 TikTok. 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. Responsibilities: 1. Conduct cutting-edge research in machine learning, computer vision or natural language processing. 2. Support and incubate products with machine learning, especially state-of-the-art AIGC techniques such as GPT, Stable Diffusion, etc.

Minimum Qualifications: 1. Final year or recent graduates in Computer Science, engineering or quantitative field 2. Rich research experience in but not limited to the following areas (as the first author of published papers at CVPR, ICCV, ECCV, TPAMI, IJCV, ICML, NeurIPS, ICLR, ACL, EMNLP, NAACL, - Image/video search, classification, and recognition - Object detection, segmentation, and tracking - Representation learning (multi-modality, pre-training, vision transformer, - OCR - Image/video/multimodal generative models - Large language models By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https:///legal/privacy If you have any questions, please reach out to us at