Responsibilities

1. Enhance existing recall, pre-ranking, ranking, and re-ranking modules in our large-scale ads platform, and continuously improve ad quality.

2. Iterate ads core models, including but not limited to CTR/CVR, expand and optimize feature set, search and create new model architecture.

3. Optimize ads bidding, billing and traffic allocation strategies to create better ads bidding mechanisms and increase ads monetisation efficiency.

4. Focus on the research of recommendations 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++ /Python, has good knowledge of data structures and algorithms

• Deep understanding of machine learning and deep learning theory, publications in machine learning and data mining or related conferences are a bonus

• Sensitive to data and business, passionate about technical challenges, and has excellent critical thinking skills

• Be familiar with big data processing tools, and 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