Machine Learning Engineer

Summary

Join the Search Ads team to work on large-scale distributed storage and architecture, NLP, Rank, and IR related problems. Responsibilities include developing an Ads system, optimizing relevance models, working on NLP capabilities, improving CTR/CVR models, researching Ads pacing algorithms, and partnering with product managers.

Requirements

• Experience with one or more general purpose programming languages including but not limited to: Go, C/C++, Python
• Experience with one or more of the following: Machine Learning, Deep Learning, NLP, ranking systems, recommendation systems

Responsibilities

• Participate in the development of a large-scale Ads system
• Responsible for relevance model and strategy optimization, such as semantic matching models, active learning, text/photo/video multi-model, ranking strategy, etc
• Participate in the development and iteration of Ads algorithms by using Machine Learning
• Work on NLP (Natural Language Processing) capability improvement and query understanding, such as query classification, seq2seq, NER (Named Entity Recognition), knowledge graph, bidword optimization, etc
• Work on CTR/CVR model estimation accuracy, data analysis, modeling, feature engineering
• Research and develop Ads pacing algorithms, ads traffic control, etc

Preferred Qualifications

1+ years of experience in and a good understanding of one of the following domains: Search, Ads, Recommendation, Monetization Products, Shopping Products