Machine Learning Scientist - Natural Language Processing
At SoundHound Inc., we believe every brand should have a voice. As the leading innovator of conversational technologies, we’re trusted by top brands around the globe. Houndify, our independent Voice AI platform, with 70,000+ users, allows brands to create custom voice assistants that deliver results with unprecedented speed and accuracy.
Our mission is to enable humans to interact with the things around them in the same way we interact with each other: by speaking naturally. We’re making that a reality through our SoundHound music discovery app and Hound voice assistant and through our strategic partnerships with brands like Mercedes-Benz, Hyundai, Deutsche Telekom, and Pandora. Today, our customized voice AI solutions allow people to talk to phones, cars, smart speakers, mobile apps, coffee machines, and every other part of the emerging ‘voice-first’ world.
Our diverse team of engineers, UX/UI designers, writers, data scientists and linguists are all passionate about creating a world with more conversations. With more than 14 years of expertise in voice technology, we have hundreds of millions of end users, and a worldwide team in six countries building solutions for a voice-first world.
About the Role:
- This is a fantastic opportunity to join the core group working on Speech Recognition at SoundHound
- Research state-of-the-art methods in Language Modeling and related Natural Language Processing problems: Text Segmentation, Language Classification etc
- Collaborate with Machine Learning engineers to prototype novel methods and productionize promising methods
- Good understanding of Machine Learning algorithms
- Proficient in one of Python or Java or C++
- Ability to write clean and efficient code
- Research work/publications in the area of Natural Language Processing
- Ph.D in Computer Science, Computational Linguistics or related fields
Nice to Haves:
- Experience training Deep Neural Network Models on GPU clusters
- Research work/publications in applying Deep Learning methods to Natural Language Processing
- Deep fluency with academic fields relevant to Statistical Language Modeling
- Familiarity with MapReduce/Spark and other relevant infrastructure
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