Research Scientist - Search/Recommendation/Ads - Global Frontier Tech Recruitment Program - 202[]
Core
Develop state-of-the-art machine learning models and strategies to improve user consumption experience and reshape content distribution logic using recommendation large models, multimodal large models, and Agentic Rec frameworks.
Role type
Research Scientist (Search/Recommendation/Ads)
Builds
Recommendation large models, unified multimodal semantic spaces, and agentic recommendation systems
Domain
Social media, content recommendation, multimodal AI
Deliverable
production ML models
Required skills
Deep learning, reinforcement learning, NLP, multimodal learning, algorithmic design, gradient convergence optimization, representation drift mitigation, self-reflection mechanisms, tool invocation, long-horizon planning
Preferred skills
Publications in top-tier conferences (ACL, EMNLP, NeurIPS, ICML, ICLR, CVPR)
Technologies
Large language models, multimodal models, agentic frameworks
Responsibilities
Address challenges in ultra-long behavioral sequences for recommendation models; explore alignment across video, image-text content, and user intent; develop recommendation agents with autonomous planning capabilities
Seniority
PhD level researcher
