Senior Audio Enhancement and Signal Processing Engineer

    • Toronto, Canada

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:

  • Lead high-impact speech enhancement projects with the potential to reach two billion end users
  • Perform R&D to design innovative audio signal processing technologies for speech enhancement
  • Implement and evaluate signal processing algorithms

Requirements:

  • Experience with DSP algorithms, especially in the context of audio. Understanding of Fourier transforms, discrete signals, filter design.
  • Strong programming skills using C++
  • Working knowledge of MATLAB
  • MS or PhD in Computer Science or Electrical Engineering or Applied Mathematics or equivalent
  • 5+ years of relevant industry experience

Nice-to-Haves:

  • Experience working with automatic speech recognition systems
  • Experience with speech enhancement, such as noise reduction, acoustic echo cancellation, gain control, microphone arrays, beamforming, or source separation
  • Knowledge of machine learning and familiarity with machine learning frameworks, such as Caffe, Tensorflow, Torch, PyTorch, MxNet, etc.


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