Senior Machine Learning Engineer, Speech Recognition

  • SoundHound Inc
  • Berlin, Germany
  • 20/11/2020
Full time Data Science Machine Learning Big Data Data Management Statistics

Job Description

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:

  • Innovate on state-of-the-art deep learning systems for speech recognition and speaker recognition
  • Apply deep learning techniques to improve acoustic models and keyword spotting

Requirements:

  • 5+ years of relevant industry experience
  • MS / PhD in Computer Science or Electrical Engineering or Statistics or equivalent
  • Understanding of modern machine learning techniques
  • Experience with Deep Learning / Neural Network frameworks such as Tensorflow, PyTorch, Caffe, Torch, MxNet, etc.
  • Strong programming skills on Linux using C++ and/or Python
  • Solid knowledge of algorithms and probability / statistics

Nice-to-haves:

  • Experience working with automatic speech recognition systems
  • Experience working with speaker recognition and keyword spotting, including wake-up phrase detection
  • Experience in computer vision and pattern recognition
  • Knowledge of DSP principles, noise reduction, echo cancelation