Senior Speech ML Engineer - Real-World AI Impact

voize; Kraków; Hybrid; PLN 180,000 - 260,000; Full time

Benefits offered by this job

Stock options

30 vacation days + birthday off

Germany Transport Ticket

Urban Sports Club

Learning platforms: Blinkist and Audib

Free language courses

Flexible working hours

Hybrid setup

Job summary

voize is building AI companions to simplify digital workflows for frontline workers. As a Machine Learning Engineer experienced with Speech recognition, you will design, train, evaluate and deploy deep learning models that power our AI companion, train models with real data, and ship new features to production daily.

You will work on end-to-end ML processes, including productionization, monitoring and optimization, with Python and PyTorch, and contribute to fast inference on mobile and hosted

Qualifications

• Hands-on experience in deep learning for speech recognition, including ASR development and optimization.
• Strong foundation in STT system development for real-world applications.
• Experience owning the ML process end-to-end: concept to production, monitoring and optimization.
• Shipped ML models to production using Python and PyTorch.
• Strong software engineering: clean code, tests, guardrails.

Responsibilities

• Design, train, evaluate and deploy deep learning models for speech recognition.
• Improve a diverse family of speech models across languages and products.
• Engineer fast inference on mobile devices and hosted environments.

Skills

Deep Learning for speech recognition

STT (Speech-to-Text) systems

ML process end-to-end

Python

PyTorch

Software engineering

Job description

voize is building AI companions to simplify digital workflows for frontline workers. As a Machine Learning Engineer experienced with Speech recognition, you will design, train, evaluate and deploy deep learning models that power our AI companion, train models with real data, and ship new features to production daily.

You will work on end-to-end ML processes, including productionization, monitoring and optimization, with Python and PyTorch, and contribute to fast inference on mobile and hosted