Applied Scientist II, Trustworthy Shopping Experience (TSE)

Are you excited about taking innovative AI solutions from proof-of-concept to production? If so, we have an exciting opportunity for you on Amazon's Trustworthy Shopping Experience (TSE) team.\n\nAt 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. We give customers 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.\n\nAs an Applied Scientist, you will lead the development of next Gen AI solutions to automate complex manual investigation processes at Amazon scale. You will work on some of the most fascinating challenges in applied AI-building systems that reason and act autonomously, learn rich representations from structured and relational data without extensive labels, adapt rapidly from limited examples, improve through feedback and interaction, seamlessly connect visual and textual understanding, and compress complex model capabilities into efficient, deployable systems. Your innovations will deliver significant impact to cost-of-serving customers while maintaining the highest standards of trust and safety.\n\nThis role offers end-to-end ownership-from initial research and proof-of-concept through production\ndeployment.

You will see your innovations serving hundreds of millions of customers within months, not years.\n\nKey job responsibilities\n• Design and build expertise deep agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with long term as well as short term memory mechanisms.\n• Design and build expertise agentic AI systems with multi-step reasoning, autonomous task execution, and multimodal intelligence with capabilities to handle feedback with long term as well as short term memory mechanisms.\n• Productionize large scale models built on top of SFT (Supervised Finetuning) and RFT (Reinforced fine tuning) approaches (GRPO with RLVR, Process/Outcome Reward Models), few shot approaches (Contrastive, Prototypical) based on multimodal datasets\n• Enhance on existing Automatic prompt optimization techniques (GEPA & beyond) towards agentic optimization given the ground truth datasets to improve agentic planning.\n• Build novel production ready Finetuned transformer architectures (using LORA/Q-LORA/LLM-JEPA etc) and conventional supervised & unsupervised ML solutions to aid the multiple potential automation requirements\n• Identify customer and business problems at project level; invent or extend state-of-the-art approaches for complex LLM workflows involving unstructured text, documents, images, and relational data\n• Author or co-author research papers for peer-reviewed venues; serve as PC member at conferences when aligned with business needs\n• Prototype rapidly, iterate based on feedback, and deliver components at SDE 1+ level that integrate directly into production-scale systems\n• Engineer efficient systems balancing model capability, deployment cost, and resource usage; write significant code demonstrating technical excellence and maintainability\n• Scrutinize algorithm and software performance for improvements; resolve root causes leaving systems more maintainable\n• Contribute to tactical and strategic planning-team goals, priorities, and roadmaps-while providing architectural guidance for AI systems\n• Participate in engineering best practices with rigorous peer reviews; communicate design decisions clearly and participate in science reviews\n• Train new teammates & interns on component construction and integration; mentor less experienced scientists and participate in hiring processes\n\nAbout the team\nInvestigation 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.\nBASIC QUALIFICATIONS:\n- 3+ years of building models for business application experience\n- PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience\n- Experience in patents or publications at top-tier peer-reviewed conferences or journals\n- Experience programming in Java, C++, Python or related language\n- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing\nPREFERRED QUALIFICATIONS:\n- Experience using Unix/Linux\n- Experience in professional software development\n\nOur inclusive culture empowers Amazonians to deliver the best results for our customers.

If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.]]>