Sr. Applied Scientist, Trustworthy Shopping Experience (TSE) Ops Product team
Are you excited about solving complex business problems at scale through GenAI? Are you fascinated about the application of Agentic AI and LLMs on real-life scenarios? Are you looking to invent solutions that drive Autonomous Artificial Intelligence? If so, we are looking for you to fill a challenging position on Amazon's Trustworthy Shopping Experience (TSE) team.
At TSE, our vision is to guarantee customers a worry-free shopping experience by earning their trust that the products they buy are safe, authentic, and compliant with regulations and policy, and giving them the confidence that Amazon stands behind every product and will make it right in the rare chance anything goes wrong. We do this in close partnership with our selling partners and empower them with best-in-class tools and expertise required to offer a high-quality selection of compliant products that customers trust. When we do this consistently, we help selling partners grow their business and power their long-term success. As a Senior Applied Scientist on the team, you will be responsible for delivering the science solutions required to automate complex manual investigation processes, especially by leveraging LLMs. You will handle Amazon scale use-cases with significant impact to the cost of serving Customers. Key job responsibilities- You invent and design new solutions for scientifically-complex problem areas and/or opportunities in existing or new business initiatives.
- You design experiments and define the science approach to solve critical business use-cases for automating manual work that involves unstructured text, documents, images, symbols, etc.
- Your work focuses on ambiguous problem areas at the product level, where the business problem or opportunity may not yet be crisply defined.
- You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty.
- You provide a system-wide view and design guidance for solutions that can be brand new or evolve from existing ones.
- You apply and set the example for best practices in software engineering, and systematically peer review code written by your team members.
- You set standards and proactively drive components to use and improve on state-of-the-art techniques.
- You autonomously drive thoughtful discussions with customers, engineers, and scientist peers, and build consensus on larger projects and factor complex efforts into independent tasks that can be performed by you and others. About the team
Investigation technology Product team in TSE is responsible for the human-in-the-loop products and technology used in the risk investigations at Amazon. The team is also responsible for reducing the cost of performing the investigations, by automating wherever possible and optimizing the experience where manual interventions are needed. The team leverages state-of-the art technology and GenAI to deliver the products and associated goals. BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience with prompting techniques for LLMs
- 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.
- PhD in math/statistics/engineering or other equivalent quantitative discipline
- Experience with conducting research in a corporate setting
- Experience in patents or publications at top-tier peer-reviewed conferences or journals.
Posted: June 11, 2025 (Updated about 6 hours ago)
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Posted: June 10, 2025 (Updated 1 day ago)
Posted: June 10, 2025 (Updated 1 day ago)
Posted: June 10, 2025 (Updated 2 days ago)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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