The Data Scientist in Natural Language Processing (NLP) within the Customer Engagement Technology, Self-Service and Automation team will work on the research, design, and implementation of solutions to key challenges in developing, evaluating, and deploying solutions based on large pretrained language models into conversational Artificial Intelligence (AI) systems that can understand and communicate with customers in a natural and contextually appropriate manner.
This role involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation, and the assessment of dialogue quality and style of the conversational model.
Key job responsibilities
- Define and implement robust HITL strategies to effectively expedite the Large Language Model (LLM) model scaling process.
- Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures.
- Analyze feedback loops and iterate on model performance to ensure continuous improvement.
- Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges.
- Document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing.
- Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate Large Language Model-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 conversational AI systems.
- Conduct experiments and evaluations to measure system and model performance, and identify areas for improvement.
- Stay up-to-date with the latest advancements in Natural Language Processing (NLP),LLMs, and conversational Artificial Intelligence (AI), and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.
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:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
About 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 develop associate-facing products that support our customer service associate workforce.
This role involves model development in areas such as multi-turn dialogue management, knowledge grounding, and open-ended generation, and the assessment of dialogue quality and style of the conversational model.
Key job responsibilities
- Define and implement robust HITL strategies to effectively expedite the Large Language Model (LLM) model scaling process.
- Collaborate with human annotators and subject matter experts to establish clear guidelines and quality control measures.
- Analyze feedback loops and iterate on model performance to ensure continuous improvement.
- Conduct in-depth analysis of large-scale conversational datasets to identify patterns, trends, and potential challenges.
- Document methodologies, findings, and results in a clear and concise manner, ensuring reproducibility and knowledge sharing.
- Collaborate with cross-functional teams, including applied scientists, software engineers, and product managers, to integrate Large Language Model-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 conversational AI systems.
- Conduct experiments and evaluations to measure system and model performance, and identify areas for improvement.
- Stay up-to-date with the latest advancements in Natural Language Processing (NLP),LLMs, and conversational Artificial Intelligence (AI), and explore opportunities to incorporate new techniques and technologies into Amazon's customer service solutions.
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:
1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan
About 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 develop associate-facing products that support our customer service associate workforce.