Applied Scientist II, Customer Service AI
The Applied Scientist plays a critical role in researching, developing, and implementing solutions to key challenges in developing conversational AI systems that understand and communicate with customers in a natural and contextually appropriate manner. This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation.
Key Responsibilities
? Research and development of LLM-based chatbots and conversational AI systems for customer service applications.
? Design and implement state-of-the-art NLP and ML models for tasks such as language understanding, dialogue management, and response generation.
? Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to integrate LLM-based solutions into Amazon's customer service platforms.
? Develop and implement strategies for data collection, annotation, and model training to ensure high-quality and robust performance of the chatbots.
? Conduct experiments and evaluations to measure the performance of the developed models and systems, and identify areas for improvement.
? Stay up-to-date with the latest advancements in NLP, LLMs, and conversational AI, and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.
? Collaborate with internal and external research communities, participate in conferences and publications, and contribute to the advancement of the field.
A Day in the Life
We thrive on solving challenging problems to innovate for our customers. By pushing the boundaries of technology, we create unparalleled experiences that enable us to rapidly adapt in a dynamic environment. Our decisions are guided by data, and we collaborate with engineering, science, and product teams to foster an innovative learning environment.
About the Team
Our team develops and deploys LLM-based Conversational AI systems to enhance Amazon's customer service experience and effectiveness. We work on innovative solutions that help customers solve their issues and get their questions answered efficiently, and associate-facing products that support our customer service associate workforce.
Basic Qualifications
- Master's degree
- 2+ years of building machine learning models or developing algorithms for business application experience Preferred Qualifications
- PhD
- 3+ years of building machine learning models or developing algorithms for business application experience
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