The Amazon Search team creates powerful, customer-focused search and advertising solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, the Amazon Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day. Our Search Relevance team works to maximize the quality and effectiveness of the search experience for visitors to Amazon websites worldwide.
The Product Search organization’s mission is to help customers efficiently find anything they are looking for. This charter requires us to build solutions that go beyond lexical matching and semantically understand the intent of the customer. Helping customers succeed in their mission helps us to earn their trust and win their loyalty. This is a rare and exciting opportunity, which is at the intersection of lucrative business opportunity, innovative research and a tremendous learning opportunity. The ideal candidate will have experience building machine learning models and information retrieval systems at scale. Additionally, we are seeking candidates with strong rigor (in engineering and applied sciences), creativity, and great judgement.
This team will work on building and improving the fundamental text analysis systems used in the search system from query processing to document processing. We focus on systems that are adaptable to multiple languages, use data to learn from changes in customer vocabulary usage, and provide analysis upon which applications needing simple tokenization through complex semantic analysis can be built. Our technology is used in high performance, large scale distributed systems, so experience developing software for mission critical latency sensitive systems is preferred.
Bachelors of Science degree in Computer Science, Engineering, Mathematics or related discipline.
At least 2 years of experience with machine learning systems.
At least 2 years of experience building web based production software.
Hands on development experience in C++, Java, and Python.
Masters or PhD in Computer Science, dealing with natural language processing.
Experience working with the Lucene search ecosystem.
Strong Computer Science fundamentals in data structures, algorithm design and complexity analysis.
Ability to read/write multiple human languages a plus.
Experience with web-scale data processing.
Technically deep in the principles of building large-scale machine learning systems.
Self-directed, flexible, goal oriented and strong sense of ownership.
Strong verbal and written communications skills; experience presenting complex technical information, succinctly, to technical and non-technical audiences.