商业生成式排序模型算法工程师（J94995）
Core
Develop and deploy end-to-end generative ranking models for commercial advertising scenarios using Transformer architectures and sequential expression paradigms to optimize CTR, CVR, and GMV.
Role type
Senior IC machine-learning engineer (generative ranking)
Builds
Next-generation commercial advertising generative ranking models and multimodal large model capabilities
Domain
Advertising, Recommendation Systems, Generative AI
Deliverable
production ML models
Required skills
Generative models, Deep learning (Transformers), Large language models, Semantic modeling, End-to-end training, Long-sequence modeling, Industrial-scale distributed inference optimization, Sequence user modeling, Semantic ID modeling
Preferred skills
Complex advertising/recommendation/search scenario practice, Multimodal semantic capability migration, Reinforcement learning, Adversarial learning, High-level academic papers, Core technology patents, Large recommendation system experience
Technologies
Python, C++, TensorFlow, PyTorch
Responsibilities
Research cutting-edge training/inference techniques and attention/quantization algorithms for efficient search and recommendation deployment, Collaborate cross-functionally to drive model innovation and business integration, Propose innovative solutions to support technical competitiveness and business foresight
Seniority
Senior, hands-on IC
