On-Device Voice AI Scientist

Amazon Science; Województwo pomorskie; Presencial; PLN 208.000 - 249.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Pension plans

Health insurance

Life insurance

Disability insurance

MultiSport card

Employee assistance program

Descripción de la vacante

Amazon Science is seeking an Applied Scientist to research and develop production-ready speech generation models optimized for constrained on-device environments. You will guide the full model lifecycle from experimentation to integration on real devices, aiming to improve offline voice experiences across devices.

The role requires a PhD in a quantitative field and experience with cutting-edge deep learning, model optimization, and on-device deployment.

Formación

• PhD in engineering, computer science, mathematics or equivalent quantitative field.
• Experience applying theoretical models in an applied environment.
• Experience with state-of-the-art deep learning architectures and optimization.

Responsabilidades

• Design and develop end-to-end ML models for on-device speech generation.
• Research generative AI, model compression, and distillation for constrained hardware.
• Propose and validate scientific approaches with detailed specs and publications when appropriate.
• Evaluate model performance and iterate training/inference pipelines for quality and efficiency.
• Collaborate with cloud and device teams to deploy research prototypes into product experiences.

Conocimientos

Python

Java

C++

Deep learning

ML knowledge

Educación

PhD in engineering

PhD in computer science

PhD in mathematics

Herramientas

TensorFlow

PyTorch

Descripción del empleo

Amazon Science is seeking an Applied Scientist to research and develop production-ready speech generation models optimized for constrained on-device environments. You will guide the full model lifecycle from experimentation to integration on real devices, aiming to improve offline voice experiences across devices.

The role requires a PhD in a quantitative field and experience with cutting-edge deep learning, model optimization, and on-device deployment.