Member of Technical Staff, Artificial General Intelligence

The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Member of Technical Staff with a strong deep learning background, to build industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Member of Technical Staff with the AGI team, you will support the development of algorithms and modeling techniques to advance the state of the art with LLMs. You will support the foundational model development in an applied research role, including model training, dataset design, and pre‑ and post‑training optimization. Your work will directly impact our customers in the form of products and services that make use of GenAI technology. You will leverage Amazon’s heterogeneous data sources and large‑scale computing resources to accelerate advances in LLMs. About the team The AGI team has a mission to push the envelope in GenAI with LLMs and multimodal systems, in order to provide the best possible experience for our customers. BASIC QUALIFICATIONS PhD, or Master’s degree and 1+ years of experience in CS, CE, ML or related field. Experience with neural deep learning methods and machine learning. 1+ years of building models for business application. Experience programming in Java, C++, Python or related language. PREFERRED QUALIFICATIONS PhD in Computer Science, Computer Engineering, Machine Learning or related field. Strong experience with Generative Artificial Intelligence (GenAI) technologies and Large Language Models (LLMs). Experience with patents or publications at top‑tier peer‑reviewed conferences or journals. Experience with popular deep learning frameworks, including PyTorch. Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. #J-18808-Ljbffr