Sr. Applied Scientist, Alexa International

Amazon Amazon · Big Tech · Turin, Italy · Machine Learning Science

The Senior Applied Scientist will focus on developing novel algorithms and modeling techniques for multilingual speech generation, text-to-speech synthesis, and speech-to-speech models within the Alexa International team. This role involves driving scientific strategy, influencing partner teams, and delivering solutions that enhance voice experiences across multiple languages, leveraging large-scale computing resources and addressing challenges in low-resource language settings.

What you'd actually do

  1. develop novel algorithms and modeling techniques to advance the state of the art in multilingual speech generation, text-to-speech synthesis, and speech-to-speech models
  2. drive cross-team scientific strategy for speech quality across international locales
  3. influence partner teams, and deliver solutions that have broad impact across Alexa's global products
  4. leverage Amazon's heterogeneous data sources and large-scale computing resources to accelerate advances in speech synthesis, voice quality, and pronunciation accuracy for non-English locales
  5. tackle complex challenges in low-resource language settings, excel at delivering impactful solutions while iterating based on customer feedback

Skills

Required

  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning
  • Experience in building machine learning models for business application
  • Several Years of experience in Applied Research
  • PhD or Master's degree

Nice to have

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

What the JD emphasized

  • strong background in speech models (understanding and generation)
  • multilingual systems
  • speech-to-speech models
  • low-resource language settings

Other signals

  • multilingual systems
  • speech-to-speech models
  • Generative AI technology
  • low-resource language settings