DESCRIPTION

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

The Speaker ID (Voice Recognition) team enables Alexa to provide personalized experience to millions of Alexa customers. Our mission is to make Alexa devices become your best friends, recognizing your voice with confidence. At core, we use both statistical, deep learning, and neural network models to make the magic happen. We are the brains behind "Alexa, who am I?" "Echo, call my mom?" and more. We help millions of Alexa customers to get personalized experience 24 hours a day, 7 days a week.

As a Software Development Engineer for the Alexa Speaker ID team focused on Speaker Recognition, you will be responsible for the design, development, testing, and deployment of scalable distributed services with high level of operational excellence. You help define product features, drive the system architecture, and spearhead the best practices that enable a quality product. In this role, you will work with scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility. The team operate in an Agile/Scrum environment to deliver high quality software against aggressive schedules.

In addition, you will build automated machine learning workflows with configurability, traceability, recoverability to enable faster experimentation. You will also partner with scientists and other engineers to help invent, implement, and connect sophisticated algorithms to our cloud based runtime engines. You will bring software best practices rigor to the machine learning domain by enabling continuous integration, continuous deployment of software artifacts. Prior domain knowledge including Machine Learning, ASR, and NLU is a preferred, though not required. However, strong motivation to learn ML, ASR and NLU is critical for successful candidates. Candidates should also be very agile in developing flexible software with respect to scientific, experimentation methods and usage patterns.

BASIC QUALIFICATIONS

• 3+ years of programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
• 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
• 4+ years of professional software development experience

PREFERRED QUALIFICATIONS

• Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, or related technical field
• Prior domain knowledge in Machine Learning, ASR, and NLU is a preferred
• Experience defining system architectures and exploring technical feasibility trade-offs
• Academic and/or industry experience with standard ML techniques, training pipelines, Neural Net frameworks
• Strong verbal/written communication, including the ability to effectively communicate with both business and technical teams
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

Amazon is an Equal Opportunity Employer - Minority / Women / Disability / Veteran / Gender Identity / Sexual Orientation / Age.