The Amazon Search team creates high impact, customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product 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 Search Relevance team focuses on several technical areas for improving search quality. In this role, you will leverage your strong background in Computer Science, Deep Learning and Generative AI to help build the next generation of our model development and assessment pipeline, harness and explain rich data at Amazon scale, and provide automated insights to improve machine learned models for ranking. The relevance improvements you make will help millions of customers discover the products they want from a catalog containing millions of products. You will work on problems such as predicting the popularity of new products, developing new ranking features and algorithms that capture unique characteristics, and analyzing the differences in behavior of different categories of customers. The work will span the whole development pipeline, including data analysis, prototyping, A/B testing, and creating production-level components.
Joining this team, you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world’s leading Internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California.
Please visit https://www.amazon.science for more information.
Key job responsibilities
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 search ranking.
- 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.
- Excellent opportunities, and ample support, for career growth, development, and mentorship.
- Competitive compensation, including relocation support.
