商业化算法工程师（J106569）
Core
Develop and optimize commercialization algorithms for search and recommendation scenarios, focusing on recall, ranking, creative, bidding, and pricing mechanisms to maximize ad revenue and ecosystem health.
Role type
Senior IC machine-learning engineer (advertising & recommendation)
Builds
Production ranking models, bidding strategies, and ad delivery systems for a search/recommendation platform
Domain
Internet advertising, search, and recommendation systems
Deliverable
production ML models
Required skills
CTR/CVR estimation, ranking learning (LTR), multi-task/multi-objective modeling, deep learning, C++/Go, TensorFlow/PyTorch, large-scale sparse feature modeling, large model SFT fine-tuning, big data processing (Spark/Hadoop/Flink), A/B testing design
Preferred skills
Reinforcement learning, PID control systems, sequence modeling, business sensitivity
Technologies
C++, Go, TensorFlow, PyTorch, Spark, Hadoop, Flink
Responsibilities
Design and optimize ad bidding mechanisms and pricing strategies (oCPC/oCPM), balance user experience with commercial value through ad-natural result fusion and frequency control, lead end-to-end optimization from data to online service, conduct A/B experiments and effect attribution
Seniority
Senior, hands-on IC
