DESCRIPTION

Deep learning is one of the most exciting areas of research, combining machine learning, statistics, optimization, data science and engineering. Key to its success are open-source libraries in areas such as Computer Vision, Natural Language Processing, Time Series Analysis, Graph Processing and Reinforcement Learning. They serve both as a means for reproducible research and as toolkits for efficient deployment.

We are looking for bright and motivated interns to join us in advancing and contributing to the open source ecosystem. Our goal is to improve these toolkits by adding advanced
and novel algorithms to them. Your mission is to implement state of the art algorithms and to invent new ones, releasing them as open source, contributing to publications, and sharing with the academic community world-wide.

The AWS Shanghai AI Lab owns research and development of DGL (Deep Graph Lab), the leading open-source platform in this new and exciting area. The research profile centered around deep graph neural network is rich, and covers 1) theoretical analysis and understanding, 2) high performance and highly-scalable core infrastructure, 3) important sub-domains model research and development (recommender system, anti-fraud, knowledge graph, drug discovery, temporal graph, computer vision, natural language and information extraction), all the way to 4) customer engagement and prototyping.

In addition, AWS Shanghai AI Lab supports research works in AWS globally. Interns will work on other key open-source projects including GluonCV, GluonNLP, GluonTS, Deep Numpy, AutoML, TVM, etc. In addition to daily interactions with the team in AWS Shanghai Lab, you will also have the opportunity to interact with world class scientists in and around Shanghai as well as world class experts elsewhere in AWS, such as Matthias Bethge, Alex Smola, Stefano Soatto, Pietro Perona, Bernhard Schölkopf, George Karypas, David Wipf, Mu Li and Zheng Zhang.

We welcome applications throughout the year, and from all regions in and outside of China.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. For individuals with disabilities who would like to request an interpreter or any support on-site, please inform our team.

BASIC QUALIFICATIONS

Machine learning direction. Experience with deep learning and neural networks, computer vision, natural language processing, recommender systems, knowledge graphs, time series analysis and statistical modeling are preferred.
System direction. Experience with distributed and network system, CPU/GPU parallel programming, compiler optimization are preferred.

PREFERRED QUALIFICATIONS

• Research experience related to machine learning, deep learning, NLP, computer vision
• Published and/or presented papers at ICASSP, ICML, NIPS, KDD, CVPR or similar top-tier conferences and events.