About the role

Role: Machine Learning Engineer (Voice)

You will take ownership of the full machine learning lifecycle for voice/speech-related learning experiences—driving development from experimentation through deployment and ongoing monitoring.

Key Missions

Own the end-to-end ML modeling pipeline: training, experimentation, deployment, and monitoring.
Collaborate with Product teams to design innovative learning experiences and measure the efficacy of production models.
Build and maintain data infrastructure, including:
- training/evaluation datasets
- labeling pipelines

Requirements

Proven experience owning ML pipelines end-to-end, from POC to production.
Strong product sense and the ability to think cross-functionally about model quality in the context of user experience.
Proficiency in Python and common deep learning frameworks such as PyTorch.
Ability to communicate complex ML concepts to non-technical stakeholders.
Experience training large models on GPUs and deploying custom deep learning models.
Experience with speech or audio.

Nice to Have

A passion for language learning and education (explicitly mentioned as a plus).

About Speak

Speak is focused on language learning and education, building technology that delivers learning experiences. The company leverages machine learning to develop and deploy models that support education-focused products and measure their impact in production.