About the job
The Amazon Search team creates customer-focused search solutions and technologies. The Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide. In this role, you will invent universally applicable signals and algorithms for training machine-learned ranking models. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products.
Responsibilities
Analyze the data and metrics resulting from traffic into Amazon's product search service.
Design, build, and deploy effective and innovative ML solutions to improve search ranking.
Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR.
Qualifications
Minimum
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred
Experience using Unix/Linux
Experience in professional software development
Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
Experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch