Speech and accent coaching app for non-native English speakers. Backed by Y Combinator.
About the role
You will be joining a top-notch machine learning team, who are striving to push forward what’s possible in speech and audio AI, but also care about creating practical uses for their work. An example of our team’s research can be found here: Accents in Latent Spaces . Our team is also behind the viral hit: BoldVoice Accent Oracle , which has been tried more than 50m times, by users all over the world.
What they're looking for
- You have a strong foundation in machine learning, statistics and mathematics, and take pride in building systems that work well and make it into production
- You thrive on solving challenging problems, and bring equal parts creativity and focus to methodically try out both proven and unproven techniques
- You care about user experience and are driven to create technologies that make a real difference
- You want to work fast, you want to not get interrupted by meetings, and you want to not need to ask for permission to do things
- Experience in Automatic Speech Recognition (ASR) will be particularly useful, as will knowledge of phonetics and the ability to discern sounds and accents
- Proficiency in Python and frameworks like TensorFlow, PyTorch, or similar
More about this role
BoldVoice helps the 1 billion global non native English speakers speak English with clarity and confidence, so they can advance their careers and lives.
The app gives users instant pronunciation feedback from speech AI, and then teaches them how to improve with video lessons and training exercises, developed by Hollywood accent coaches.
Today, BoldVoice is one of the top Education apps on the App Store and serves non-native speakers of 100+ different language backgrounds all over the world.
💻 About the Role
As a Machine Learning Engineer / Researcher at BoldVoice, you’ll play a critical role in driving the development and optimization of our AI systems. Your work will directly enhance the user experience by creating new machine learning-enabled capabilities, and improve the accuracy and efficacy of our existing machine learning systems. Specifically, you’ll work on:
- Designing, training, and fine-tuning machine learning models for AI coaching, pronunciation feedback, and accent detection. This will include working on LLMs, speech models like Wav2Wec2.0, and multi-modal models like speech to speech models.
- Deploying these models into production environments for real-time and...
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