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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, not only English and major languages of Europe, but also Turkish, Arabic, Japanese, and more. The team plays a central role in search query understanding, product indexing, and representations/embeddings of queries and products, all of which aid in improving the ranking and relevance of search results.
This is a rewarding role where you will be able to draw a clear connection between your work and how it improves the experience of millions of Amazon customers across the globe every day. You will propose and explore publication-worthy 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:
· 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 various components of the search stack, such as indexing, ranking, and query understanding
· 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
Your benefits include:
· Working on a high-impact, high-visibility product, with your work improving the experience of millions of customers
· The opportunity to use (and innovate) state-of-the-art ML methods to solve real-world problems
· Being part of a growing team where you can influence the team's mission, direction, and how we achieve our goals
· Excellent opportunities, and ample support, for career growth, development, and mentorship
· Competitive compensation, including relocation support (for both domestic and international candidates)
· 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
· At least one publication, as first author, in a leading conference or journal related to machine learning, natural language processing, or information retrieval
· 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 (German is not required)
No candidate is perfect, and we do not expect you to meet all, or even most, of the qualifications below. If you have one or more of these qualifications, we will be very excited to receive your application!
· PhD degree (or significant progress towards completing it) in a quantitative field
· 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
· Fluency in one or more languages other than English
Amazon Science (www.amazon.science) gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://amazon.jobs/en/privacy/eu) to know more about how we collect, use and transfer the personal data of our candidates.