Machine Learning Engineer, Voice
Hybrid (San Francisco)$200k - $300kFull-timePosted 11mo ago
About the role
Experience-driven ML Engineer role focused on developing and deploying speech recognition and related models to support Speak's language learning platform. End-to-end ownership of modeling pipelines, collaboration with Product, and impact on user learning experiences.
Responsibilities
- Training and deploying ASR models end-to-end, including monitoring, performance tracking, and retraining
- Improving the pronunciation model that provides precise feedback, and make it more central to our learning app
- Creating metrics to measure ASR performance across tasks and languages
- Expanding our ASR systems to new languages and markets
- Building and maintaining data infrastructure such as training/evaluation datasets and labeling pipelines
Qualifications
- Extensive experience training large models on GPUs and deploying custom deep learning models
- Proficiency in Python and common Deep Learning frameworks like PyTorch
- Demonstrated experience owning ML pipelines end to end, from POC to production
- Strong communication skills and the ability to explain complex ML concepts to non-technical stakeholders
- Sharp product sense and an ability to think broadly and cross-functionally about model quality in the context of user experience
Skills
Required:Training large ML modelsPython programmingML pipelinesCommunicationProduct sense
Nice to have:Speech/audio (bonus)
Last updated Jul 29, 2026. Interested? Apply on the company site.
About Speak
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