Amazon Search JP builds features powering product search on the Amazon JP shopping site and expands the innovations to world wide. As an Applied Scientist on this growing team, you will take on a key role in improving the NLP and ranking capabilities of the Amazon product search service. Our ultimate goal is to help customers find the products they are searching for, and discover new products they would be interested in. We do so by developing NLP components that cover a wide range of languages and systems.
As an Applied Scientist for Search JP, you will design, implement and deliver search features on Amazon site, helping millions of customers every day to find quickly what they are looking for. You will propose innovation in NLP and IR to build ML models trained on terabytes of product and traffic data, which are evaluated using both offline metrics as well as online metrics from A/B testing. You will then integrate these models into the production search engine that serves customers, closing the loop through data, modeling, application, and customer feedback. The chosen approaches for model architecture will balance business-defined performance metrics with the needs of millisecond response times.
Your responsibilities include:
· Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching, ranking and Search suggestion problems.
· Analyzing data and metrics relevant to the search experiences.
· Working with teams worldwide on global projects.
· Master's degree in a quantitative field (computer science, electrical engineering, mathematics, physics, or similar)
· 3+ years of post-Master's hands-on experience (academic or industrial) building ML models
· Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning
· Strong coding and problem-solving skills in at least one programming language such as Python, Java, C++, etc.
· Fluency in written and spoken English (Japanese is not required)
· PhD degree (or significant progress towards completing it) in a quantitative field
· At least one publication, as first author, in a leading conference or journal related to machine learning, natural language processing, or information retrieval
· Prior work experience as an applied scientist or a data scientist at a consumer product company
· Prior work experience on a multidisciplinary team of scientists and engineers
· Experience using an object-oriented language (Java, C++, or equivalent) to write production-ready code
· Experience using deep learning libraries such as TensorFlow or PyTorch, particularly to solve NLP tasks
· Experience with search engines, particularly indexing, ranking, and query understanding