Alexa is the Amazon cloud service that powers Echo, the groundbreaking new Amazon device designed around your voice. Voice is the most natural user interface for interacting in the home and is quickly becoming the preferred way to seek information on any topic, at any time, from any place. Whether in the kitchen with Echo, on the couch with Fire TV, or on the go with mobile, customers expect Alexa to delight them with immediate and accurate answers to their questions.
The Knowledge Engineer is responsible representing real-world objects and concepts in ways that both computers and people can understand. The Knowledge Engineer will work across and within our content areas including weather, geography, history, movies, sports, music, science, math, literature, business, politics, traffic and more. The successful candidate will work to maintain the quality of knowledge already in the system, and expand the capabilities of the platform to infer new knowledge. He or she will work with teams of developers and machine learning scientists to enhance the existing technology and invent new knowledge ingestion techniques.
Alexa uses proprietary technology, therefore, the successful candidate can expect full training without needing specific experience in the area. However it's a complex and demanding role, requiring a lot of raw talent and versatility to learn the full system and quickly become productive across all areas.Responsibilities
- Analyse data schemas and knowledge design to track and resolve issues that in turn empower Alexa to answer more questions
- Expand Alexa’s ability to translate questions and answers between natural language and the system’s internal information representation and vice versa
- Identify new areas of knowledge, and represent these real-world objects and concepts in Alexa
- Maintain the quality of knowledge already in the system
- Work with teams of developers to enhance the existing technology
- Have direct responsibility for question answering success metrics
- Derive insights from functional processes, and identify opportunities to automate and improve operations
- Partner with internal stakeholders and product managers to create and review Knowledge Engineering sprint planning