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Sr. Applied Scientist, Classification and Policy Platform

Amazon

Sr. Applied Scientist, Classification and Policy Platform

full-timePosted: Aug 13, 2026Updated: Aug 27, 2026Seattle, Washington, United States

Job Description

Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations. The Classification and Policy Platform team is looking for Sr. Applied Scientists to build technology to automatically monitor the billions of products on the Amazon platform. The software and processes built by this team are a critical component of building a catalog that our customers trust. You will have an opportunity to work with cutting edge machine learning algorithms on large datasets. You will need to build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. We are looking for highly motivated applied scientists and engineers interested in delivering the next level of innovation to product search for Amazon. As an Applied Scientist on the CPP team, you will be responsible for working across backend, client, business development, and data engineering teams to coordinate deep-dives, inform roadmaps, visualize metrics, and create predictive models to determine how we can best serve our customers. Responsibilities include: - 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 - Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential - 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 - Providing technical and scientific guidance to your team members - Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds - Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information.

Locations

  • Seattle, Washington, United States

Salary

167,100 - 226,100 USD / yearly

Skills Required

  • neural deep learning methodsintermediate
  • modeling tools such as Rintermediate
  • large scale distributed systems such as Hadoopintermediate

Required Qualifications

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

Preferred Qualifications

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

Responsibilities

  • 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
  • Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential
  • 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
  • Providing technical and scientific guidance to your team members
  • Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds
  • Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers

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