Applied Scientist Amazon
Seattle, WA

Job Description

The Amazon Browse Classification and Discovery team is seeking an Applied Scientist for developing ML techniques that can help classify Amazon products into our catalog and build new experiences for improving customer discovery of products. You will be part of a team of experienced Applied Scientists working on a new set of initiatives, building models and delivering them into the Amazon production ecosystem. Your efforts will build a robust ensemble of ML techniques that can drive classification of products with a high precision and scale to new marketplaces and languages. This problem is challenging due to sheer scale (billions of products in the catalog), diversity (products ranging from electronics to groceries to instant video across multiple languages) and multitude of input sources (millions of sellers contributing product data with different quality).

Do you want the excitement of experimenting with cutting edge machine learning, natural language processing and artificial intelligence techniques to solve real world problems at scale? Imagine experimenting with Deep Neural Networks as your daily job and imagine using your team's output to affect the product discovery of the biggest e-tailer in the world. Imagine leading research inside of an Amazon team that is always looking to deploy creative solutions to real world problems in product discovery. Your research findings are directly related to Amazon's Browse experience and impact million of customers. Your team will build solutions ranging from automatic detection of misclassified items in the ever growing Amazon Catalog, applications for analyzing books and identify its genre, understand music beats and movies, ingest images, text and all the unstructured attributes in the Amazon catalog to drive true understanding of products at scale.

We are looking for an experienced Applied Scientist who can develop best in class solutions. Your primary customers are Amazon shoppers who would thank you for correctly identifying products in our catalogs across countries and languages.

The ideal candidate has deep expertise in one or several of the following fields: Web search, Applied/Theoretical Machine Learning, Deep Neural Networks, Classification Systems, Clustering, Label Propagation, Natural Language Processing, Artificial Intelligence. S/he has a strong publication record at top relevant academic venues and experience in launching products/features in the industry.