广告算法工程师（信息流激励方向） - Ads Core
Core
Design and optimize incentive mechanisms within the information feed to balance user retention, engagement, and long-term LTV against advertising commercialization efficiency.
Role type
Senior IC algorithm engineer (incentive & recommendation optimization)
Builds
Real-time incentive decision systems and joint optimization frameworks for content distribution, user incentives, and ad delivery.
Domain
Social media advertising, recommendation systems, and large-scale commercial transaction mechanisms.
Deliverable
production ML models
Required skills
C++, Python, deep learning frameworks (TensorFlow, PyTorch), reinforcement learning, causal inference, multi-objective optimization, real-time bidding, large-scale online experimentation
Preferred skills
Experience in recommendation/ad/search systems, understanding of recall/ranking/bidding/traffic allocation, business abstraction and problem decomposition, hands-on project leadership
Technologies
C++, Python, TensorFlow, PyTorch, reinforcement learning, causal inference, operations research
Responsibilities
Participate in joint optimization of information feed incentives and recommendation scenarios; Model personalized incentive decisions and strategy optimization for Feed scenes; Collaborate with product and engineering teams to build incentive-recommendation linkage mechanisms; Iterate incentive decision paradigms using deep learning and optimization methods; Explore best practices for incentives in Feed scenarios and build reusable algorithmic frameworks.
