Applied Scientist II, Text-to-Speech on Device team

Amazon; Województwo pomorskie; Presencial; PLN 350.000 - 550.000; Jornada completa

Descripción de la vacante

Amazon Applied Scientist II, Text-to-Speech on Device team in Poland is responsible for researching and developing production-ready speech generation models that run locally on hardware. You will cover the full model lifecycle from experimentation to device integration, targeting offline voice experiences for Alexa and related platforms.

Ideal candidates have a PhD in a quantitative field, deep learning expertise, and a track record in model optimization and cross-functional collaboration across

Formación

• PhD in engineering, computer science, ML, mathematics or equivalent quantitative field.
• Experience applying theoretical models in an applied environment.
• Experience with state-of-the-art deep learning model architectures and optimization.
• Experience implementing algorithms using self-developed code.

Responsabilidades

• Design and develop end-to-end ML models for on-device speech generation, from early research through production-ready deployment.
• Research and apply advanced techniques in generative AI, model compression, and knowledge distillation for constrained devices.
• Propose and validate novel scientific approaches with detailed technical specifications and potential publications.
• Evaluate model performance, iterate on training and inference pipelines to optimize quality and efficiency.
• Collaborate with cloud and device teams to bring speech generation capabilities from research to integrated product experiences.

Conocimientos

PhD in engineering

Applied ML experience

DL model design

Cross-team collaboration

Educación

PhD in engineering, CS, ML, math or equivalent

Herramientas

Python

Java

C++

Descripción del empleo

Applied Scientist II, Text-to-Speech on Device team

Job ID: 10536961 | AMZN Dev Cntr Poland sp. z.o.o

Have you ever wondered how we give voice to devices — even when they're offline? The Text-to-Speech on Device team at Amazon builds AI-powered voice models that run locally on hardware with limited resources, serving customers across Alexa, automotive, and accessibility experiences for visually impaired users. We sit at the intersection of speech generation, generative AI, and on-device machine learning, and we're looking for a curious, collaborative Applied Scientist to help us push what's possible.

In this role, you will research and develop production-ready speech generation models optimized for constrained environments. You will work across the full model lifecycle — from early experimentation and prototyping through to integration on real devices. If you're excited about solving hard scientific problems that directly improve how millions of people interact with technology, we'd love to hear from you.

Key job responsibilities

• Design and develop end-to-end machine learning models for on-device speech generation, from early research and experimentation through production-ready deployment.
• Research and apply advanced techniques in generative AI, model compression, and knowledge distillation to deliver high-quality voice models within tight hardware constraints.
• Propose and validate novel scientific approaches by authoring detailed technical specifications and contributing to peer-reviewed publications when appropriate.
• Evaluate model performance rigorously, identify improvement opportunities, and iterate on training and inference pipelines to optimize quality and efficiency.
• Collaborate with science and engineering teams across cloud and device platforms to bring speech generation capabilities from research prototypes to integrated product experiences.

About the team

The Text-to-Speech on Device team builds low-footprint AI models for speech generation that run locally on devices such as Android and FireOS platforms. Our models require significantly less computation than cloud-hosted alternatives, enabling offline voice experiences for Alexa, automotive partners, and accessibility solutions. We work closely with device engineering teams and cloud-based speech science teams to deliver the best possible experience for our customers. Our focus in the coming years is expanding the range of voices and languages we support while continuing to improve naturalness and efficiency on constrained hardware.

Basic Qualifications

• PhD in engineering, computer science, machine learning, mathematics or equivalent quantitative field
• 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++

Preferred Qualifications

• Experience with model optimization techniques (quantization, distillation, compression, inference optimization etc.)
• Experience in professional software development
• Experience with Speech Generation models
• Experience working with agile development methodologies
• Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients

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The minimum gross base salary for this position is listed below. The base salary listed corresponds to working on a full-time basis. For part‑time hours, the salary will be pro‑rated.

Amazon reserves the right to offer a higher base salary, depending on the candidate's skills, competencies, and experience. Amazon's package may include a sign on payment. In addition, the candidate may be eligible to participate in a restricted stock unit scheme operated independently by Amazon.com Inc. in USA. Your recruiting team will share final salary and any restricted stock unit scheme if applicable, depending on skills and requirements.

Company supplementary benefits apply subject to further terms, including pension plans, health insurance, life and disability insurance, business travel insurance, MultiSport card, employee discount code and program (EDC/Extras), and the Employee Assistance Program (private and confidential counselling and referral service to support health and well‑being).

See below the minimum gross base salary for this position:

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