Applied Scientist - TTS Research - Amazon - Cambridge - Wizbii

Applied Scientist - TTS Research

Job description


Alexa Amazon's ground-breaking cloud service that powers devices such as Echo and FireTV. We are looking for a passionate, talented, and inventive Scientist with a strong machine learning background to join us in beautiful Cambridge, UK, to help build industry-leading Speech and Language technology. Our mission is to push the envelope in computer generated speech, computer generated characterisation and “Vactor” performance, in order to provide the best-possible experience for our customers.

As an applied scientist, you will work with talented peers to develop novel algorithms and modelling techniques to advance the “state-of-the-art” in spoken language generation. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in computer generated speech.

Position Responsibilities:
· Research and implement novel ML and statistical approaches which add value to Amazon
· Lead and Mentor junior engineers and scientists
· Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for spoken language applications
· Develop and/or apply statistical modelling methods (e.g. deep neural networks), optimizations, and other ML techniques to different applications in spoken language engineering

Seeked profile


· Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences or a related discipline with specialization in speech synthesis, recognition, natural language processing, or machine learning.
· Computer Science fundamentals in algorithm design, complexity analysis, data structures, problem solving and diagnosis.
· Familiarity with programming languages such as Python, Scala, Java, C#/.Net or C/C+.
· Good written and spoken English communication skills.

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