Senior Speech ML Engineer - Remote, Stock Options

Voize; United States; Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Stock options

30 days vacation

Birthday off

Transport ticket

Urban Sports Club

Blinkist/Audible access

Language courses

Job summary

Voize is expanding a team that builds AI companions to streamline frontline workflows. As a Machine Learning Engineer, you’ll design, train, and deploy speech-recognition models that power real-world applications across languages. You’ll ship new features to production daily and improve models in production environments.

You will own the end-to-end ML process from concept to monitoring, using Python and PyTorch, while ensuring robust software engineering practices and guardrails.

Qualifications

• Several years hands‑on experience in deep learning for speech recognition, including developing and optimising ASR systems.
• Excellent foundation in STT system development with a focus on real-world applications.
• Experience owning the ML process end-to-end: concept, productionisation, maintenance, monitoring and optimization.

Responsibilities

• Take ownership for the design, training, evaluation, and deployment of deep learning models in speech recognition.
• Models you build impact end‑user experiences directly.
• Improve a diverse family of speech models live in the field, across languages and products, with fast inference on mobile and hosted environments.

Skills

Speech recognition

ASR systems

STT development

End-to-end ML

Python

PyTorch

Software engineering

Tools

Python

PyTorch

Job description

Voize is expanding a team that builds AI companions to streamline frontline workflows. As a Machine Learning Engineer, you’ll design, train, and deploy speech-recognition models that power real-world applications across languages. You’ll ship new features to production daily and improve models in production environments.

You will own the end-to-end ML process from concept to monitoring, using Python and PyTorch, while ensuring robust software engineering practices and guardrails.