• Enhance existing recall, pre-ranking, ranking, re-ranking modules in our large scale ads platform, and continuously improve ads quality
• Iterate ads core models, including but not limited to CTR/CVR, expand and optimize feature set, search and create new model architecture
• Optimize ads bidding, billing and traffic allocation strategies to create better ads bidding mechanism and increase ads monetisation efficiency
• Focus on the research of recommendation and ads to apply relevant strategies and adapt to our platform for implementation in our production system

Requirements:
• Bachelor's degree or higher in Computer Science or a related field
• Familiar with at least one of the following programming languages, C++/Golang/Python, has good knowledge of data structure and algorithm
• Deep understanding in machine learning and deep learning theory, publications in machine learning and data mining or related conferences is a bonus
• Sensitive to data and business, passionate about technical challenges, have excellent critical thinking skills
• Be familiar with big data processing tools, have experience with one or more of the following tools: Hadoop, Spark, Hive and Flink etc.
• Effective team player and has good communication skills
• Proactive and self-motivated
• Preferred to have Ads algorithm experience