The Alexa Shopping team is looking for Applied Scientists to build the next generation of shopping assistants.
As an applied scientist in Alexa Shopping, you will be responsible for the research, design and development of new natural language, search, and machine learning technologies for voice shopping. You will be working with top scientists and engineers, as well as with product teams and other research partners, both locally and abroad. Your work will combine data mining, systems and software development, exploration of new technologies, as well as publications and presentations at top scientific conferences.
The ideal candidates have deep expertise in one or several of the following fields: Information Retrieval, Web search, Web data mining, Machine Learning, Natural Language Processing, Artificial Intelligence. An ideal candidate shows a bias for action and has a strong understanding of empirical methods. The ability to write clearly and speak convincingly as evidenced through participation in academic conferences and service in the scientific community are a must.
Amazon is an Equal Opportunity Employer – Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.
· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
· 3+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
PhD in Computer Science or equivalent Master's Degree plus 4+ years of experience in Information Retrieval, Machine Learning, or related fields · Programming proficiency in languages such as Java and Python · Peer-reviewed publications in information retrieval, natural language processing, machine learning or related topics
Experience with Local Search, Voice recommenders, Recommender Systems, Personalization, User Engagement or related topics. PhD in Computer Science with a focus on Information Retrieval, Data Mining, Web Mining, Recommender Systems, or Machine Learning · Publication in WWW, WSDM, SIGIR, RecSys, EMNLP, CIKM preferred · Industrial experience with big data, map-reduce or Spark