Applied Science Ii, Edge Technology

Amazon Amazon · Big Tech · Sunnyvale, CA · Applied Science

Develops and deploys state-of-the-art ML, NLP, DL, and CV algorithms for customer-facing industrial solutions, leveraging research and pragmatic thinking to deliver production-ready models.

What you'd actually do

  1. developing state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems
  2. bring statistical modeling and machine learning advancements to data analytics for customer-facing solutions in complex industrial settings
  3. take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking
  4. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products

Skills

Required

  • 3+ years of building models for business application experience
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience in patents or publications at top-tier peer-reviewed conferences or journals
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development
  • PhD in computer science, machine learning, engineering, or related fields
  • Research experience related to machine learning, deep learning, NLP, computer vision, sensor fusion
  • Published and/or presented papers at ICASSP, ICML, NIPS, KDD, CVPR or similar top-tier conferences and events

What the JD emphasized

  • building models for business application experience
  • patents or publications at top-tier peer-reviewed conferences or journals
  • Published and/or presented papers at ICASSP, ICML, NIPS, KDD, CVPR or similar top-tier conferences and events

Other signals

  • developing state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms
  • solve real world problems
  • deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking
  • deliver these to production in customer facing products