商业化算法工程师（J105636）
Core
Develop and optimize commercialization algorithms for search and recommendation scenarios, including recall, ranking, creative, bidding, and pricing mechanisms to maximize ad revenue and ecosystem health.
Role type
Senior IC commercial algorithm engineer (search/recommendation)
Builds
Ad ranking systems, bidding engines, and multi-objective estimation models for search and recommendation platforms
Domain
Internet advertising, search, and recommendation systems
Deliverable
production ML models
Required skills
CTR/CVR estimation, Learning to Rank (LTR), multi-task/multi-objective modeling, deep learning, C++/Go, TensorFlow/PyTorch, large-scale sparse feature modeling, large model SFT fine-tuning, Spark/Hadoop/Flink
Preferred skills
A/B experimental design, metric analysis, causal inference, reinforcement learning, PID control
Technologies
TensorFlow, PyTorch, Spark, Hadoop, Flink, C++, Go
Responsibilities
Design and optimize ad bidding mechanisms and pricing strategies (oCPC/oCPM), develop deep learning models for sequence modeling and joint modeling, balance user experience with commercial value through ad-natural result fusion, lead end-to-end optimization from data to online service, design and analyze A/B experiments for effect attribution
