Amazon - Bellevue, WA
posted 3 months ago
The Conversational AI Modeling and Learning (CAMEL) team is a vital part of Amazon's Artificial General Intelligence (AGI) organization, dedicated to creating a best-in-class Conversational AI that is intuitive, intelligent, and responsive. Our mission revolves around developing superior Large Language Models (LLM) solutions and services that enhance the capabilities embedded within the model. This enables the utilization of thousands of APIs and external knowledge sources, ultimately providing the best experience for each request across millions of customers and endpoints. We are seeking a passionate, talented, and resourceful Senior Research Scientist specializing in LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems, and/or Information Retrieval. The ideal candidate will be responsible for inventing and building scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will possess a strong machine learning background and a desire to push the boundaries in one or more of the aforementioned areas. Hands-on experience in building Generative AI solutions with LLMs is essential, along with a self-motivated approach to tackling challenging problems that deliver significant customer impact. The role requires agility in shipping solutions quickly and iterating based on user feedback and interactions. As a Senior Research Scientist, you will leverage your technical expertise and experience to demonstrate leadership in addressing large, complex problems. You will set the direction and collaborate with other talented applied scientists and engineers to research and develop LLM modeling and engineering techniques that reduce friction and enable natural and contextual conversations. Your work will involve analyzing, understanding, and improving user experiences by utilizing Amazon's heterogeneous data sources and large-scale computing resources to accelerate advancements in artificial intelligence. You will engage with core LLM technologies, including Prompt Engineering, Model Fine-Tuning, Reinforcement Learning from Human Feedback (RLHF), and Evaluation. Your contributions will have a direct impact on our customers through the development of novel products and services.