We are seeking a talented applied researcher to join the Search Suggestions team. The charter of the team is to help customers craft better searches, and serendipitously discover new experiences, by developing the most utilized search features on Amazon.com: search autocomplete and spelling correction. Our platform uses massive amounts of data and machine intelligence to generate the best possible search suggestions and spelling corrections with low latency. In this role you will use data to power novel experiences in search autocomplete and evaluate more effective algorithms for spelling correction. You will make improvements to the search autocomplete customer experience by designing and implementing machine learning and deep learning algorithms to improve ranking and candidate generation, conduct A/B tests, analyze experimental results, and launch features. You will drive features from idea to deployment and your work will directly impact millions of customers. This is a unique opportunity for a seasoned applied researcher to explore and implement ML & deep learning components in search autocomplete and spelling correction.
You Are Going To Love This Job Because You Will:
· Apply the state of art in ML (including Deep Learning) and NLP to search auto-complete and spelling correction
· Invent, design, propose, implement, and test scalable data-driven algorithms.
· Propose and implement improvements to the customer experience touching hundreds of millions of customers and run A/B experiments to measure impact
· Work in a dynamic team that provides continuous opportunities for learning and growth working with leaders in the field of machine learning
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.