Applied Scientist II, On-Device Text-to-Speech

Amazon; Województwo pomorskie; On-site; PLN 350,000 - 550,000; Full time

Job summary

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

Qualifications

• 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.

Responsibilities

• 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.

Skills

PhD in engineering

Applied ML experience

DL model design

Cross-team collaboration

Education

PhD in engineering, CS, ML, math or equivalent

Tools

Python

Java

C++

Job description

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