The Amazon Speech team is a group of scientists and developers working on audio, speech and natural language solutions that revolutionize how customers interact with Amazon’s products and services. The team’s mission is to push the envelope in automatic speech recognition (ASR) and natural language understanding (NLU) in order to provide the best possible experience for our customers. Products such as Amazon Echo
and Fire TV
are illustrative of the user-delighting spoken language solutions Amazon is building.
We are looking for passionate, inventive, and talented Machine Learning Engineers with experience in exploring innovative, high customer impact, dependable Machine Learning applications that can wow our customers. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know. You will design and develop fast, efficient, and highly scalable machine learning algorithms that are mainly applied but not limited to speech technology. Creating reliable, scalable, and high performance products requires exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, Speech Processing and practical experience building large-scale distributed systems. You will be working with other Machine Learning Engineers and SDEs in laying out technical vision for the team through brainstorming and identify most impactful Machine Learning applications for the team and focusing on areas such as forecasting, deep learning, analytics, and any new initiatives that will unveil Alexa’s true potential.Responsibilities:
- Responsible for the development and maintenance of key system features
- Will work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility.
- Will work in an Agile/Scrum environment to deliver high quality software against aggressive schedules.
- Will establish architectural principles, select design patterns and then mentor team members on their appropriate application