Applied Scientist: Conversational AI & LLMs (Hybrid)

Amazon Inc.; Santa Clara (CA); Hybrid; USD 172,000 - 222,000; Full time

Job summary

Amazon Development Center U.S., Inc. is seeking passionate Applied Scientists with a strong ML background to build industry-leading Conversational AI systems. You will work on NLU, Dialog systems and Generative AI, influencing products used by millions of customers.

You will collaborate with experts to develop novel algorithms, leverage foundation models, and apply ML to scale across large data and compute resources in AWS. Hybrid work may be available in the U.S. with flexible arrangements.

Qualifications

• 3+ years of building models for business application experience.
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience.
• Experience in patents or publications at top-tier peer‑reviewed conferences or journals.
• Experience programming in Java, C++, Python or related language.
• Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‑performance computing.

Responsibilities

• Develop novel algorithms and modeling techniques to advance language technology.
• Work on NLU, Dialog Management, Conversational AI, LLMs and Generative AI.
• Collaborate with AWS UC team to support Compute, Database, Storage and other services in AWS.

Skills

ML modeling

Programming: Java/C++/Python

Publications

Algorithms & data structures

Education

PhD or MS with 4+ years CS/CE/ML

Tools

Unix/Linux

Job description

Amazon Development Center U.S., Inc. is seeking passionate Applied Scientists with a strong ML background to build industry-leading Conversational AI systems. You will work on NLU, Dialog systems and Generative AI, influencing products used by millions of customers.

You will collaborate with experts to develop novel algorithms, leverage foundation models, and apply ML to scale across large data and compute resources in AWS. Hybrid work may be available in the U.S. with flexible arrangements.