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# Applied Scientist, Alexa-PAPI

- **Company:** Amazon.com, Inc.
- **Location:** Sunnyvale, CA, United States
- **Experience:** Experienced
- **Salary:** $171,600.0 - $222,200.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), A/B Testing, Artificial Intelligence, Amazon Alexa, Business Software, C++ (Programming Language), Python (Programming Language), Natural Language Processing, Chatbots, Large Language Models, Generative AI, Build Tools
- **Published:** August 8, 2026
- **Apply:** https://www.amazon.jobs/en/jobs/10496248/applied-scientist-alexa-papi

## About the Role

2+ 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 programming in Java, C++, Python or related language
 - Demonstrated expertise in one or more of the following areas: Natural Language Processing (NLP); Recommendation, Search, or Advertisement systems; Conversational AI

Preferred Qualifications

 - Experience prioritizing and delivering projects on time in a fast-moving environment
 - Experience communicating complex information and solutions to senior stakeholders and influencing decisions
 - Hands-on experience with RAG architectures, LLM post-training, evaluation and reasoning pipelines, agentic system design, and scalable deployment.
 - Published research (peer-reviewed publications) preferred.
 - Strong familiarity with state-of-the-art Generative AI tools and frameworks (e.g., Claude Code, Langchain, Open Claw, or equivalent).

## Description

* Advance core technology: Invent, design, and implement state-of-the-art solutions for previously unsolved problems in agentic AI, memory retrieval, and context management at scale.
 * Solve real customer problems: Build systems that learn from heterogeneous, multi-modal customer signals-conversations, device visual signals, ambient activities, purchase histories, and more-to deliver the right information, in the right format, at the right time.
 * Build for scalability: Design and deploy customer-feedback-driven, self-optimizing agentic architectures that serve millions of customers across Amazon surfaces, programs, and marketplaces.
 * Drive platform-level impact: Contribute to a platform science team responsible for organizing and reasoning over diverse customer interactions to continuously improve personalization quality.
 * Champion scientific rigor and responsible evaluation: Own the end-to-end science lifecycle-from hypothesis formulation and offline experimentation to online A/B testing and production accountability. Design evaluation that measure personalization quality and safety at scale, ensuring every launch is backed by statistically sound evidence.

This is not incremental work. You will push the boundaries of what personalized AI assistants can do-bridging research in generative AI, memory systems, and agentic reasoning with production systems that operate at Amazon on scale. Your innovations will directly shape how millions of customers experience Alexa Plus daily.


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