Applied Scientist Iii, Alexa Edge AI

Amazon Amazon · Big Tech · Boston, MA · Machine Learning Science

Applied Scientist III, Alexa Edge AI at Amazon is a research-focused role developing novel ML algorithms for speech and audio processing. Requires PhD or Master's with 7+ years of applied research experience, strong ML/deep learning background, and programming skills. Experience in speech recognition, NLP, and large-scale systems is preferred.

What you'd actually do

  1. Conduct applied research project(s) effectively and know when to ask for help and when to work independently
  2. Engage with an experienced cross-disciplinary staff to conceive and design innovative solutions for consumer products.
  3. Actively participate and contribute to research activities including publications and patents
  4. Work closely with an internal inter-disciplinary team, and outside partners to drive key aspects of product definition, execution and test.
  5. Be proactive, flexible and able to succeed within an open collaborative peer environment

Skills

Required

  • 5+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 7+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

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.
  • Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

What the JD emphasized

  • strong background in deep learning and speech processing techniques
  • novel machine learning algorithms
  • advance the state of the art in speech and audio processing
  • building speech recognition, machine translation and natural language processing systems

Other signals

  • develop novel machine learning algorithms
  • advance the state of the art in speech and audio processing
  • building speech recognition, machine translation and natural language processing systems