ML SDE - Alexa Speech

Job description

DESCRIPTION

Alexa is the groundbreaking cloud-based intelligent agent that powers Echo and other devices designed around your voice. Our mission is to push the envelope in Machine Learning (ML) for Automatic Speech Recognition (ASR), in order to provide the best-possible experience for our customers. We're looking for a Software Development Engineer to help build industry-leading conversational technologies and machine learning systems that customers love.

As a Software Development Engineer for the Alexa team, you will be responsible for translating business and functional requirements into concrete deliverables with the design, development, testing, and deployment of highly scalable distributed services. You will also partner with scientists and other engineers to help invent, implement, and connect sophisticated algorithms to our cloud based engines. Prior domain knowledge including Deep Learning and Machine Learning is a preferred, though not required. However, strong motivation to learn DL and ML is critical for successful candidates. Candidates should also be very agile in developing flexible software with respect to scientific, experimentation methods and usage patterns. Additional responsibilities include:
· Designing, developing and maintaining core system features, services and engines
· Helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product
· Working with scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility
· Operating in an Agile/Scrum environment to deliver high quality software against aggressive schedules

Desired profile

BASIC QUALIFICATIONS

· 2+ years of non-internship professional software development experience
· Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
· 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.