Senior Applied Scientist , AGI
Amazon (AI roles) · Boston, Massachusetts, USA
No salary listed. Estimated from 344 salary-disclosed Research roles on this board: $225K–$340K (interquartile range; estimate, not the employer's figure).
Apply at Amazon (AI roles)Find your warm intro on LinkedInAbout the role
Amazon's Artificial General Intelligence (AGI) organization is seeking a talented Applied Scientist to help build the next generation of large language models and conversational AI experiences. In this role, you will design, develop, and evaluate state-of-the-art machine learning models that power products used by hundreds of millions of customers worldwide. You will work with large-scale datasets, modern deep learning frameworks, and world-class scientists and engineers to take ideas from research prototype to production. This is a hands-on scientist role that combines rigorous applied research with the engineering excellence required to ship reliable, responsible AI at Amazon scale.
Key job responsibilities
- Design, implement, and evaluate machine learning and deep learning models to solve challenging problems in natural language understanding, generation, and conversational AI.
- Develop scalable training and evaluation pipelines for large language models using large, real-world datasets.
- Collaborate with scientists, engineers, and product teams to translate research advances into production systems that improve customer experiences.
- Conduct rigorous experimentation, analyze results, and iterate rapidly to improve model quality, efficiency, and safety.
- Stay current with the latest research, contribute novel ideas, and help raise the scientific bar of the team.
- Champion responsible AI practices, including evaluation for fairness, robustness, and safety.
About the team
The AGI organization at Amazon is dedicated to advancing the science and engineering of large language models and generative AI. Our teams build foundation models and the systems around them, spanning pretraining, post-training, evaluation, and responsible AI. We are a collaborative group of scientists and engineers who value scientific rigor, customer obsession, and rapid iteration, and we work on some of the most impactful AI problems at Amazon scale. - 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Key job responsibilities
- Design, implement, and evaluate machine learning and deep learning models to solve challenging problems in natural language understanding, generation, and conversational AI.
- Develop scalable training and evaluation pipelines for large language models using large, real-world datasets.
- Collaborate with scientists, engineers, and product teams to translate research advances into production systems that improve customer experiences.
- Conduct rigorous experimentation, analyze results, and iterate rapidly to improve model quality, efficiency, and safety.
- Stay current with the latest research, contribute novel ideas, and help raise the scientific bar of the team.
- Champion responsible AI practices, including evaluation for fairness, robustness, and safety.
About the team
The AGI organization at Amazon is dedicated to advancing the science and engineering of large language models and generative AI. Our teams build foundation models and the systems around them, spanning pretraining, post-training, evaluation, and responsible AI. We are a collaborative group of scientists and engineers who value scientific rigor, customer obsession, and rapid iteration, and we work on some of the most impactful AI problems at Amazon scale. - 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
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