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Machine Learning Research Scientist

Location: Mountain View, CA

Job Description:
JD Digits AI Lab at Silicon Valley, is looking for research scientists and engineers with strong background in deep learning, machine learning and big data. As a research scientist/engineer, you will be uniquely positioned in our team to work on challenging problems and advance the frontiers of AI technologies. For example, we have applied modern deep learning technologies in modeling user interactive behaviors and fine-tuned the model in the multi-task environment. We’ve built product knowledge graphs using NLP techniques and trained them using graph convolutional networks. On top of our core technologies, we are working on a large-scale autoML system that is able to generate neural networks well suited for various user-targeting scenarios and construct state-of-the-art recommendation algorithms.
 
Responsibilities:
1) Conduct applied research and development in machine learning, deep learning, and big data.
2) Research and evaluate state-of-the-art AI algorithms for user modeling, document modeling, knowledge graph, graph convolutional networks, and reinforcement learning.
3) Develop AI products for industry. Example tasks include but not limited to automatic machine learning, recommendation systems, user/item classification, user/item segmentation, etc.

Key Qualifications:
  • Ph.D. in at least one of the following field (but not limited to): 1. Machine learning/data mining: deep learning, recommendation systems, knowledge graph, reinforcement learning, large-scale optimization, information retrieval, etc. 2. Data mining: information extraction, knowledge/pattern discovery from huge-size, complex data
  • Strong analytical skills (SQL, statistics, optimization, etc.).
  • Ability to quickly prototype with practical algorithms and write high quality code in a programming language (such as Python, Java, C++).

Preferred Qualifications:
  •    Experiences in developing new algorithms with track record on top journals/conferences
  •    Experiences in integrating new techniques into the live production system
  •    Familiar with at least one of deep learning frameworks: Tensorflow, Pytorch, Caffe, Mxnet, etc.
  •    Experience with large-scale computing platform, e.g., Spark, Hadoop
  •    Finance/insurance industry experience is a plus but not required.
  •    Self-motivated and eager to learn new things.
  •    Team orientation: we work towards our goal as an agile team together, rather than individually
 
About JD Digits AI Lab (https://jddglobal.com)
JD Digits was formerly known as JD Finance before comprehensively brand escalated in November 2018. Its operational purpose is to connect finance and real industry by using digital technology, boosting the influence of the Internet, enhancing the digital and intelligent development of industries, foster the development of the real economy and create greater social value. Centered on the cutting-edge technologies including data technology, AI, IoT and blockchain, JD Digits has completed the deployment in finance, city, agriculture, campus services and digital marketing, and integrated the personal end, corporate end and government end in terms of its clients. As of June 2019, JD Digits is the second most funded Chinese FinTech and blockchain startup.

In the future, JD Digits will more deeply explore current business patterns and enter into more real industry sectors.


About JD (http://corporate.jd.com)
JD.com is the largest e-commerce company in China, and the largest Chinese retailer, by revenue. The company strives to offer consumers the best online shopping experience. Through its user-friendly website, native mobile apps, and WeChat and Mobile QQ entry points, JD offers consumers a superior shopping experience. The company has the largest fulfillment infrastructure of any e-commerce company in China. As of June 30, 2017, JD.com operated 7 fulfillment centers and 335 warehouses covering 2,691 counties and districts across China, staffed by its own employees. JD.com is a member of the NASDAQ100 and a Fortune Global company.