Applied Scientist-LLM, Buy For Me
Seattle
Friday, 01 May 2026
Do you want to shape the next generation of AI-driven customer experiences for Amazons most ground-breaking products? Join us and help invent the future of shopping. We are seeking a passionate, innovative, and highly skilled Applied Scientist with expertise in AI, Agentic LL - Ms, Generative AI, Machine Learning, and NLP to help build LLM-powered solutions for Amazons Buy. For. Me product, which enables Amazon customers to discover and purchase products from any merchants. Our team develops science and agentic AI capabilities that power a seamless, end-to-end shopping experience for Amazon customers. We build and advance technologies such as agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve pre-purchase, in-purchase, and post-purchase workflows. Key job responsibilities. As an Applied Scientist on our team, you will:Invent, implement, and evaluate state-of-the-art models and agentic systems that directly impact customer experience. Conduct research that may lead to publications, patents, or cross-Amazon technical influence. Collaborate with engineers, product managers, and other scientists to translate business challenges into scalable science solutions. Run experiments with real customer data and validate hypotheses in a high-impact product environment. Drive excellence in model performance, safety, reliability, and evaluation frameworks. Basic Qualifications- Experience programming in Java, C , Python or related language- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field. Preferred Qualifications- Experience implementing algorithms using both toolkits and self-developed code- Have publications at top-tier peer-reviewed conferences or journals- 1 years of building machine learning models or developing algorithms for business application experience- Experience in LLM finetuning, pretraining, testing, and prompt engineering.