Role OverviewThe Search Ads team constantly pushes the boundaries of general search engine monetization across our apps, building a globally leading Search Ads monetization system. As a graduate, you will have the chance to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems.
What You Will Do
You will participate in the development of a large-scale Ads system, responsible for relevance model and strategy optimization, and work on NLP capability improvement and query understanding. You will also work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering, and research and develop Ads pacing algorithms.
Why It Might Be a Fit
Successful candidates must be able to commit to an onboarding date by the end of the year. You will have opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Requirements
- Bachelor's or above degree in Computer Science, Software Engineering, Computer Engineering, or a related technical discipline
- Experience in and good theoretical grounding in machine learning concepts and techniques
- Excellent programming, debugging, and optimization skills in one or more general purpose programming languages
- Experience in one or more of the following frameworks: Tensorflow/PyTorch/MXNet, etc
- Ability to think critically and to formulate solutions to problems in a clear and concise way
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