Applied Scientist II, TTS on Device
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Monthly Salary:
Posted on:
22 hours ago
Vacancies:
1 Vacancy
Job Summary
Do you want to join the team working on the bleeding edge technology Have you ever wondered how we can give voice to the devices Or join the team developing GenAI models
Our team is working on all of the above join us to see yourself. Text-to-Speech on Device team is responsible for development AI based voice models working locally on the devices. This require specific mix of skills between devices integration voice generation technologies and machine learning.
We are delivering solutions for multiple customers including offline solutions for Alexa automotive customers and accessibility voices for visually impaired users. All our models are integrated for devices and working with limited hardware resources.
Key job responsibilities
We are looking for an Applied Scientist with experience in building highly optimized Machine Learning models for speech generation.
As an Applied Scientist you will:
- Work with the team on end-to-end development of an ML models for speech generation from early experimentation to building production ready models
- Engage in state-of-the-art and innovative research in areas such as Speech Generation Gen AI model compression and knowledge distillation
- Invent optimization techniques to push the boundaries of deep learning model training and inference
- Create and propose detailed theoretical specifications for novel research ideas and directions and rigorously justify their correctness
- Train custom Speech Generation and Gen AI models that beat the state-of-the-art and paves path for developing production models
- Collaborate with other science teams to bring state-of-the-art Speech Generation models from cloud to devices
About the team
Text-to-Speech on Device team is focused on delivery of low-footprint AI models for speech generation that can work locally on devices (Android FireOS etc.). These models require much less computation power then the ones hosted in cloud. We are cooperating directly with the teams developing devices and with scientists responsible for the cloud models in order to provide our customers best possible experience.
- PhD in engineering computer science machine learning mathematics or equivalent quantitative field
- Experience working in Speech Science
- Experience applying theoretical models in an applied environment
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience implementing algorithms using toolkits and self-developed code
- Experience with programming languages such as Python Java C
- Experience with model optimization techniques (quantization distillation compression inference optimization etc.)
- Experience in professional software development
- Experience communicating across technical and non-technical audiences including executive level stakeholders or clients
- Experience working with agile development methodologies
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our team is working on all of the above join us to see yourself. Text-to-Speech on Device team is responsible for development AI based voice models working locally on the devices. This require specific mix of skills between devices integration voice generation technologies and machine learning.
We are delivering solutions for multiple customers including offline solutions for Alexa automotive customers and accessibility voices for visually impaired users. All our models are integrated for devices and working with limited hardware resources.
Key job responsibilities
We are looking for an Applied Scientist with experience in building highly optimized Machine Learning models for speech generation.
As an Applied Scientist you will:
- Work with the team on end-to-end development of an ML models for speech generation from early experimentation to building production ready models
- Engage in state-of-the-art and innovative research in areas such as Speech Generation Gen AI model compression and knowledge distillation
- Invent optimization techniques to push the boundaries of deep learning model training and inference
- Create and propose detailed theoretical specifications for novel research ideas and directions and rigorously justify their correctness
- Train custom Speech Generation and Gen AI models that beat the state-of-the-art and paves path for developing production models
- Collaborate with other science teams to bring state-of-the-art Speech Generation models from cloud to devices
About the team
Text-to-Speech on Device team is focused on delivery of low-footprint AI models for speech generation that can work locally on devices (Android FireOS etc.). These models require much less computation power then the ones hosted in cloud. We are cooperating directly with the teams developing devices and with scientists responsible for the cloud models in order to provide our customers best possible experience.
- PhD in engineering computer science machine learning mathematics or equivalent quantitative field
- Experience working in Speech Science
- Experience applying theoretical models in an applied environment
- Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience implementing algorithms using toolkits and self-developed code
- Experience with programming languages such as Python Java C
- Experience with model optimization techniques (quantization distillation compression inference optimization etc.)
- Experience in professional software development
- Experience communicating across technical and non-technical audiences including executive level stakeholders or clients
- Experience working with agile development methodologies
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover invent simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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