Applied Scientist II, Artificial General Intelligence, AGI Information
Role details
Job location
Tech stack
Job description
We are looking for a passionate, talented and inventive Applied Scientist to develop industry-leading Generative Artifical 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 new methods and algorithms for inference-time scaling in the field of agentic search.
If you are deeply familiar with LLMs, NLP and ML 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 as well as business stakeholders to maximize velocity and impact of your team's contributions.
It's an exciting time to be a leader in AI research. In Amazon's AGI Information team, you can make your mark by improving information-driven experience of Amazon customers worldwide!
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.
Requirements
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 in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications
Preferred Qualifications
- Experience using Unix/Linux
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience in professional software development
- Experience building machine learning models or developing algorithms for business application
- Experience with training and evaluating LLMs
