Machine Learning Researcher

Job Summary

To support the development of cutting-edge voice technology, the full-time Machine Learning Researcher in Audio will engage in foundational research and development of speech-to-text, text-to-speech, and neural audio codecs, working either remotely or from San Francisco.

Key Responsibilities

• Design and train large-scale text-to-speech models and neural audio codec architectures
• Build and fine-tune robust automatic speech recognition systems for various real-world scenarios
• Develop scalable training pipelines and run rigorous experiments to validate modeling approaches

Required Qualifications

• Experience with self-supervised learning, multimodal modeling, or generative modeling
• Hands-on experience in building or scaling TTS, STT, or neural audio codec systems
• Familiarity with large-scale speech datasets and real-world audio variability
• Knowledge of inference optimization techniques and real-time constraints in telephony
• PhD in ML, AI, or a related field, or equivalent research impact is preferred