Applied Scientist, Perfect Order Experience (POE) AI

Applied Scientist, Perfect Order Experience (POE) AI

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Applied Scientist, Perfect Order Experience (POE) AI Job ID: Services LLC At Amazon, we believe scientific innovation is the cornerstone of being the world's most customer centric company. The Perfect...

Applied Scientist, Perfect Order Experience (POE) AI

Job ID: Services LLC

At Amazon, we believe scientific innovation is the cornerstone of being the world's most customer centric company. The Perfect Order Experience (POE) AI team is at the forefront of this innovation, building scalable scientific solutions that ensure flawless customer experiences while empowering sellers and brands worldwide. As a part of our team, you'll be pioneering the development of agent based intelligent systems that identify and prevent abuse and infringement, protecting millions of customers globally.

In this role, you'll have access to Amazon's vast computational resources and latest AI technologies, allowing you to push the boundaries of what's possible in LLM development. While solving complex real-world problems, you'll maintain your academic connections through publications and conference participations. Our team culture encourages both independent research and collaborative problem solving, creating an environment where you can thrive professionally while making a significant impact on our customers. Working alongside talented scientists, economists, and engineers, you'll have the freedom to innovate while seeing your solutions deployed at an unprecedented scale.

Key job responsibilities
  1. Design and develop advanced AI systems using LLMs and machine learning for infringement and abuse prevention at scale.
  2. Build automated AI solutions that emulate human decision making capabilities.
  3. Conduct data analysis and translate insights into practical ML solutions.
  4. Collaborate with cross functional teams to implement and scale solutions.
  5. Own end to end solution development from conception to production deployment.
About the team

Here at Selling Partner Services, we embrace our differences. We are committed to furthering our culture of inclusion. We have 14 employee led affinity groups, reaching 10,000+ employees in chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our DEI Ambassador Program. Amazon's culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Basic Qualifications
  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
  • 3+ years of building models for business application 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.
Preferred Qualifications
  • Experience applying theoretical models in an applied environment.
  • Experience in state of the art deep learning models architecture design and deep learning training and optimization or model pruning.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit for more information.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit

This position will remain posted until filled. Applicants should apply via our internal or external career site.

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