广告算法工程师（算力&流量方向）-Data
Core
Build end-to-end compute-aware and traffic distribution models using deep learning to optimize ROI for ad requests across recall, ranking, and bidding stages.
Role type
Senior IC machine-learning engineer (advertising & compute optimization)
Builds
Real-time ad traffic distribution and compute resource scheduling systems
Domain
Online advertising, recommendation systems, reinforcement learning
Deliverable
production ML models
Required skills
deep learning, reinforcement learning, optimization, Python, C++, PyTorch, TensorFlow, large language models, multi-agent systems
Preferred skills
experience in recommendation systems, value estimation (LTV/ROI), decision transformers, PPO, offline RL, agentic workflows
Technologies
PyTorch, TensorFlow, LLMs, Multi-Agent systems
Responsibilities
Design reward functions and robust learning mechanisms for sparse feedback scenarios; Integrate LLMs for adaptive compute tuning and intelligent traffic routing; Research foundational models for agentic workflows in large-scale recommendation systems.
Seniority
Senior, hands-on IC
