Conversational AI ModEling and Learning (CAMEL) team is part of Amazon Device organization where our mission is to create a best-in-class Conversational AI that is intuitive, intelligent, and responsive, by developing superior Large Language Models (LLM) solutions and services which increase the capabilities built into the model and which enable utilizing thousands of APIs and external knowledge sources to provide the best experience for each request across millions of customers and endpoints.
We are looking for a passionate, talented, and resourceful science leader in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have solid technical background and extensive experience in leading projects and technical teams. The ideal candidate would also have experiences in developing natural language processing systems (particularly LLM based systems) for industry applications, enjoy operating in highly dynamic and ambiguous environments, be self-motivated to take on challenging problems to deliver customer impact.
In this role, you will lead a team of scientists to fine tune and evaluate the LLM to improve instruction following capabilities, align human preferences with RLHF, enhance conversation responses with RAG techniques, and various other. You will use your management, research and production experience to develop the team, communicate direction and achieve the results in a fast-paced environment. You will have significant influence on our overall LLM strategy by helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product.
Key job responsibilities
Key job responsibilities
Build a strong and coherent team with particular focus on sciences and innovations in LLM technologies for conversation AI applications
Own the strategic planning and project management for technical initiatives in your team with the help of technical leads. Provide technical and scientific guidance to your team members.
Collaborate effectively with multiple cross-organizational teams. Communicate effectively with senior management as well as with colleagues from science, engineering and business backgrounds.
Support the career development of your team members.
We are looking for a passionate, talented, and resourceful science leader in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. A successful candidate will have solid technical background and extensive experience in leading projects and technical teams. The ideal candidate would also have experiences in developing natural language processing systems (particularly LLM based systems) for industry applications, enjoy operating in highly dynamic and ambiguous environments, be self-motivated to take on challenging problems to deliver customer impact.
In this role, you will lead a team of scientists to fine tune and evaluate the LLM to improve instruction following capabilities, align human preferences with RLHF, enhance conversation responses with RAG techniques, and various other. You will use your management, research and production experience to develop the team, communicate direction and achieve the results in a fast-paced environment. You will have significant influence on our overall LLM strategy by helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product.
Key job responsibilities
Key job responsibilities
Build a strong and coherent team with particular focus on sciences and innovations in LLM technologies for conversation AI applications
Own the strategic planning and project management for technical initiatives in your team with the help of technical leads. Provide technical and scientific guidance to your team members.
Collaborate effectively with multiple cross-organizational teams. Communicate effectively with senior management as well as with colleagues from science, engineering and business backgrounds.
Support the career development of your team members.