Amazon AI Research Scientist
hace 3 días
About the Role
As an Applied Scientist at Amazon, you will be part of a dynamic and entrepreneurial environment that pushes the boundaries of Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs). Your role will involve working on innovative projects that encompass language understanding, Retrieval-Augmented Generation (RAG), semantic parsing, code generation, and agentic workflow. You will collaborate with internationally recognized experts to develop novel algorithms and modeling techniques, directly impacting millions of customers through AWS products and services while contributing to the wider research community.
Your Key Responsibilities
- Develop novel algorithms and modeling techniques in NLP, Generative AI, LLM, NLU, and Agentic workflows.
- Conduct innovative research and influence the science roadmap and direction of the team.
- Collaborate with internationally recognized experts to advance human language technology.
- Apply rigorous research methods to respond to large-scale NLP needs with efficient and scalable solutions.
- Leverage Amazon's vast data sources and large-scale computing resources to accelerate advances in language understanding.
- Contribute to the wider research community through publications in top-tier conferences and journals.
Benefits and SalaryWe offer a competitive salary range for this role: $160,000 - $220,000 per annum. Our benefits package includes comprehensive health insurance, 401(k) matching, and generous paid time off. This role offers the chance to interact closely with customers and the academic community, publish your work in top-tier conferences and journals, and be at the heart of AWS's growing and exciting AI focus area.
About AmazonAmazon is a global leader in e-commerce, cloud computing, digital streaming, and artificial intelligence. We are committed to innovation and customer obsession. As an Applied Scientist at Amazon, you will have the opportunity to work with Amazon's vast array of text and structured data sources, as well as access to large-scale computing resources to accelerate advancements in language understanding.
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