Applied ML Engineer, Speech
Job Description
Speak is revolutionizing language learning through AI-powered tutoring, having raised over $150M from prestigious investors including OpenAI, Accel, Founders Fund, and Khosla Ventures. As the #1 language learning app in South Korea, they're expanding globally across 15+ languages. They're seeking an experienced Machine Learning Engineer to develop cutting-edge speech recognition models for language learning. The role involves end-to-end ownership of modeling pipelines, from training to deployment, and close collaboration with Product teams to create innovative learning experiences. The position offers the opportunity to work with a dynamic team on ASR, assessment, pronunciation, and content personalization projects. The company maintains offices in San Francisco, Ljubljana, Seoul, and Tokyo, providing a truly global work environment. They offer competitive compensation ($170K-$280K plus equity) and the chance to make a significant impact on millions of learners worldwide. The ideal candidate should have strong experience in deep learning, Python proficiency, and excellent communication skills. This role presents an exciting opportunity to join at a crucial growth phase and contribute to transforming how people learn languages globally.
Responsibilities For Applied ML Engineer, Speech
- Training and deploying ASR models end-to-end, including monitoring, performance tracking, and retraining
- Improving the pronunciation model that provides precise feedback
- Creating metrics to measure ASR performance across tasks and languages
- Expanding ASR systems to new languages and markets
- Building and maintaining data infrastructure such as training/evaluation datasets and labeling pipelines
Requirements For Applied ML Engineer, Speech
- 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 ability to explain complex ML concepts to non-technical stakeholders
- Sharp product sense and ability to think broadly about model quality in user experience context
- Experience with speech or audio (bonus)
Benefits For Applied ML Engineer, Speech
- Equity
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