Applied Scientist - Business Integrity - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Description

We are looking for talented individuals to join our team in 2027. 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 2027. Please state your availability and graduation date clearly in your resume.

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 Applied Scientists 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.

Topic Content: With the explosive growth of digital content, intelligent moderation has become a core capability for internet platforms. However, as moderation scenarios grow increasingly complex and adversarial tactics continue to evolve, traditional approaches are facing unprecedented challenges. The current landscape is characterized by multiple technical difficulties, including the dynamic nature of moderation rules, content complexity, sample scarcity, escalating adversarial behaviors, and a lack of interpretability. In particular, existing open-source large models often do not perform as effective as we expect in scenarios involving evolving moderation rules, long-form text, long temporal sequences, multilanguages, limited sample data, and adversarial content generated by AIGC.

Requirements

Minimum Qualifications:
1. Individuals who are completing or have recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
2. Modeling experience in one or more of the areas: Ads, Search engine, Recommender System, NLP/CV, multimodal, agent technologies.
3. 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 LLM application and deployment.
4. Strong publications record in top conferences (e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, N
CVPR, ICCV, and ECCV)