Sr. Applied Scientist, Classification and Policy Platform

Amazon Amazon · Big Tech · Seattle, WA · Applied Science

Applied Scientist role focused on building machine learning models and technology to automatically monitor and classify billions of products in the Amazon catalog, ensuring compliance and safety. The role involves working with large datasets, deep learning for search matching and ranking, filtering, indexing, and document understanding, with a focus on delivering customer-facing experiences at Amazon scale.

What you'd actually do

  1. Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding
  2. Conducting and coordinating process development leading to improved and streamlined processes for model development.
  3. Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps
  4. Providing technical and scientific guidance to your team members
  5. Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds

Skills

Required

  • 3+ years of building machine learning models for business application experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning
  • PhD, or Master's degree and 6+ years of applied research experience
  • 4+ years of applied research experience

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

  • build technology to automatically monitor the billions of products
  • Amazon scale applications
  • state-of-art deep learning
  • search matching and ranking problems
  • apply document understanding
  • machine learned models

Other signals

  • building technology to automatically monitor billions of products
  • machine learning algorithms on large datasets
  • Amazon scale applications running on Amazon Cloud
  • state-of-art deep learning to solve search matching and ranking problems
  • filtering, new content indexing, and apply document understanding