About the job
Amazon serves hundreds of millions of customers. Each one has a unique history of purchases, preferences, and behaviors. Our team's mission: turn that history into real-time contextual intelligence that makes every Amazon experience feel personal.
We're hiring an Applied Scientist to push the boundaries of what's possible with LLMs, semantic retrieval, and customer understanding at scale.
The problem space: Imagine a system that can instantly synthesize years of customer signals — what they bought, what they love, what they're planning — and surface the exact right context for any experience, in milliseconds. That's what we build. It's equal parts information retrieval, generative AI, and systems engineering.
Responsibilities
Invent new approaches to contextual retrieval, relevance scoring, and LLM-based summarization.
Fine-tune and evaluate language models for domain-specific understanding.
Design experiments that measure real customer impact, not just benchmark scores.
Ship production systems and iterate based on live metrics.
Collaborate across teams — Alexa, Search, Recommendations — as a platform that powers them all.
Mentor team members and shape the technical direction of our roadmap.
Qualifications
Minimum
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 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 in designing experiments and statistical analysis of results
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Preferred
Experience using Unix/Linux
Experience in professional software development