Applied Scientist, Artificial General Intelligence, AGI Information

We are looking for a passionate, talented and inventive Applied Scientist to develop industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs). In this role, you will innovate in the fastest-moving fields of current AI research, in particular developing foundation models capable of processing a broad range of information in many languages.
If you are deeply familiar with LLMs, NLP and ML, and driven to scale GenAI across a broad range of languages, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams across AGI, as well as business stakeholders to maximize velocity and impact of your team’s contributions.

Key Job Responsibilities

• Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results.
• Build solutions that address customer needs, making informed trade-offs to balance accuracy, efficiency, and user experience.
• Work with peers to develop novel algorithms or modeling techniques to advance the state of the art with LLMs.

About the Team

The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Company:

Amazon

Qualifications:

BASIC QUALIFICATIONS

• PhD, or a Master’s degree and experience in CS, CE, ML or related field.
• Experience in designing experiments and statistical analysis of results.
• Experience programming in Java, C++, Python or related language.
• Experience with deep learning methods, machine learning, natural language processing or machine translation.

PREFERRED QUALIFICATIONS

• Experience using Unix/Linux.
• Experience in patents or publications at top-tier peer-reviewed conferences or journals.
• Experience with popular deep learning frameworks such as MxNet and Tensor Flow.
• Experience in professional software development.
• Experience building machine learning models or developing algorithms for business application.
• Hands-on experience in training and evaluating LLMs.

Educational Level:

Master Degree