Recruitment

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    Please email us with your CV and the position you are interested in applying.

    Email: jiaqiufang@jd.com

Scientist in Machine Learning

Location:

Beijing / Mountain View, California

Job Description:

Research on data-driven descriptive and predictive machine learning models leveraging the large amount of data from JD.com to improve customer experience. Areas include, but not limited to: deep learning, reinforcement learning, statistical learning, kernel method,feature selection, etc.
Design and implement machine learning models for commercial applications.

Scientist in Natural Language Processing

Location:

Beijing / Mountain View, California

Job Description:

Research and development in natural language processing (NLP), including, but not limited to, text classification/clustering, named entity identification, sentence boundary disambiguation, question answering, lexical semantics, machine translation, etc.
Apply NLP approaches in business and products to improve customer experience and minimize the cost for human interactions.

Scientist in Computer Vision

Location:

Beijing / Mountain View, California

Job Description:

JD.com has a large variety of data for research and analysis. All products at JD.com have pictures and descriptions. Researchers in computer vision will work on object recognition, image/video processing, analysis, indexing, retrieval, classification and compression,etc.
Our researchers bring core computer vision expertise to commerce, and combine computer vision and machine learning techniques for large-scale image/video data.

Scientist in Information Retrieval

Location:

Beijing / Mountain View, California

Job Description:

We are refining a personalized Information Retrieval system to provide high quality and interesting products to customers. Based on the previous customer behaviors, the system matches the query, customer and candidate products for accurate rankings.
Process textual/multi-media data and build index in big data environment.
Use appropriate evaluation metrics to measure the performance of the retrieval system

Scientist in Speech Recognition

Location:

Beijing / Mountain View, California

Job Description:

Research and develop novel algorithms for speech recognition including acoustic models, language models, and other automatic speech recognition (ASR) related technologies.
Implement speech recognition models in JD’s Al platform (PinoAl), and English/Chinese LVCSR system.

Scientist in Data Mining

Location:

Beijing / Mountain View, California

Job Description:

The data mining team is developing advanced statistical and machine learning methods for applications across all of products at JD.com. This role will conduct research on data mining and related fields.
The responsibilities include: discover interesting patterns/knowledge, and create insights from big data.

Scientist in Applied Operation Research

Location:

Beijing / Mountain View, California

Job Description:

Optimization team builds optimization models and analytic tools that improve the efficiency of the company’s supply chain.
We solve challenging problems in inventory, distribution, and delivery systems. Collaborating closely with the Development and Business teams, we build data driven models to solve real business problems, and further guide and drive business development.

Scientist in Recommender System

Location:

Beijing / Mountain View, California

Job Description:

Recommender systems are playing an increasingly important role in e-commerce portals. Based on the massive data from JD.com, we are building a novel recommendation model into China’s largest online retailer with the most advanced technologies in the industry.
Our recommendation model has been applied on JD mall and JD App to help hundreds of millions of JD users. As such, our team has strong ties internally to product groups as well as externally to the research community.
Our research team (http://datascience.jd.com) at JD.com are working on that the foundations of JD.com recommendation technologies are at or above the state of the art and, in the process, redefine the state of the art for the field.
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