Looking to make an impact on the future of global commerce? Do you want to shape how millions of people buy, sell, and engage around the world?
The Search Query Understanding team is the biggest contributor to eBay’s search / query processing and drives a significant portion of revenue.
We are growing at a rapid pace and committed to building a stellar team. We are a team where people who think and do things differently and win are rewarded and grow.
Our team is results-oriented and hardworking. We are building solutions for core e-commerce search problems such as query rewriting, query annotation / classification, query recovery with state-of-the-art ML algorithms tailored to understand large-scale user behavioral signals.
The environment is friendly and fun. We get things done that make a difference.
We are looking for stellar applied researchers to join us and build the next generation of query understanding products in eBay search.
If you enjoy the scale and technical complexity of query processing (understanding query intent, entity resolution and tagging, categorization, intelligent query rewrites and clustering, application of knowledge graph, to name a few) and want to be at the frontier of applied research in e-commerce, join now.
Help us redefine query understanding at eBay.
Seek scientifically valid solutions that deliver real value to eBay customers
Build machine learning models and data pipelines to deliver insightful yet practical solutions
Work with multiple teams to help promote standard scientific methodologies and processes in your field
Present key technical and novel research work in public forums and conferences
MS or PhD in Computer Science, Statistics, Mathematics, or equivalent
PhD or 1-3 years (with MS) of industrial experience in a related field
Experience with one or more of the following : classification, regression, NLP, GBM, recommendation systems, clustering, fraud detection, DeepLearning / Neural Networks, or related
Experience in big data processing, e.g. Hadoop, SQL, Spark
Experience with Python or R, and Java or Scala or C / C++
Optional) Related publications in quality conferences or journals