Applied Scientist - Monetization GenAI - Global Frontier Tech Recruitment Program - 2027 Start (PhD)

Responsibilities

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: We are the Generative AI team under Monetization Technology. Our team focuses on developing cutting-edge Generative AI techs across all modalities, including text, image, videos, landing pages, etc., and creates industry-leading technical solutions to improve creative efficiency for advertisers, agencies and creators. We are committed to automated creative workflows by leveraging Generative AI technologies, to increase overall revenue for advertisers, agencies and creators.

Topic Content: Short-form videos have become a core format for ads placement. To significantly improve automation in production, this topic aims to build an intelligent agentic closed-loop system based on TopAds. The system is designed to deeply analyze viral multimodal narratives and camera motion rythms, and automatically orchestrate in-house models to seamlessly integrate new products for efficient replication of successful content. It further seeks to move beyond traditional open-loop generation by introducing real ads placement signals as key feedback. Through reinforcement learning (RL), placement data is directly fed back to continuously optimize the agent's decision-making strategies across the full pipeline, including video understanding, controllable generation, and low-performing content filtering and replacement.
Ultimately, the system aims to enable scalable production of high-ROI marketing videos.

Responsibilities:
In this role, you will build an intelligent ad delivery system optimized for user Long-Term Value (LTV) and long-term ROAS, achieving an optimal balance between commercial value and user experience.

Qualifications

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)