Amazon
Applied Scientist
Amazon, Seattle, Washington, us, 98127
Job ID: 2719471 | Amazon.com Services LLCThe Applied Scientist in NLP within Customer Engagement Tech, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing conversational AI systems based on large pretrained language models, that can 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 and assessment of dialogue quality and style of the conversational model.Key job responsibilities
Lead the 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 and dialogue quality assessment.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.If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:Medical, Dental, and Vision CoverageMaternity and Parental Leave OptionsPaid Time Off (PTO)401(k) PlanAbout the team
Join our team of scientists and engineers who develop and deploy 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
3+ years of building machine learning models or developing algorithms for business application experiencePhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceExperience in patents or publications at top-tier peer-reviewed conferences or journalsExperience programming in Java, C++, Python or related languageExperience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)PREFERRED QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative fieldExperience in professional software developmentAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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This involves tackling complex problems in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation and assessment of dialogue quality and style of the conversational model.Key job responsibilities
Lead the 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 and dialogue quality assessment.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.If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!Benefits Summary
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:Medical, Dental, and Vision CoverageMaternity and Parental Leave OptionsPaid Time Off (PTO)401(k) PlanAbout the team
Join our team of scientists and engineers who develop and deploy 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
3+ years of building machine learning models or developing algorithms for business application experiencePhD, or Master's degree and 4+ years of CS, CE, ML or related field experienceExperience in patents or publications at top-tier peer-reviewed conferences or journalsExperience programming in Java, C++, Python or related languageExperience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)PREFERRED QUALIFICATIONS
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative fieldExperience in professional software developmentAmazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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