Senior Applied Scientist - Deep Learning
- Gdańsk, Poland
Our team undertakes research together with multiple organizations to advance the state-of-the-art in speech technologies. We not only work on giving Alexa, the ground-breaking service that powers Echo, her voice, but we also develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video. Do you want to be part of the team developing the latest technology that impacts the customer experience of ground-breaking products? Then come join us and make history.
We are looking for a passionate, talented, and inventive Senior Applied Scientist with a background in Machine Learning, to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Text-to-Speech (TTS) in order to provide the best-possible experience for our customers.
As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and modelling techniques to drive the state of the art in speech synthesis.
• Participate and lead the design, development, evaluation, deployment and updating of data-driven models for text-to-speech applications.
• Participate in research activities including the application and evaluation of text-to-speech techniques for novel applications.
• Research and implement novel ML and statistical approaches to add value to the business.
• Mentor junior engineers and scientists.
• PhD degree with 4 years of applied research experience or a Master's degree and 6+ years of experience of applied research experience.
• Comprehensive and deep knowledge in fields such as Machine Learning, Deep Learning, TTS, ASR, NLU or Statistical modelling with at least one publication, as first author, in a leading conference or journal related to one of these fields.
• Good written and spoken communication skills.
• PhD with specialization in text-to-speech, natural language processing, or machine learning.
• Extensive experience in developing speech synthesis and natural language processing models (e.g., commercial speech products or government speech projects).
• Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
• Hands on experience with machine learning frameworks such as MXNet, TensorFlow, or PyTorch.
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