Applied Scientist, Customer360
Listed on Amazon’s official careers site. Posted October 15, 2026. Check that it is still open and apply there.
Apply on Amazon’s careers site →Job description
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.
Why this role
1.
Scale
Your models will serve 1,500+ requests per second across Amazon's largest surfaces.
2.
Impact
Direct revenue attribution in the hundreds of millions — your work shows up in customer experiences the same week.
3.
Frontier tech
Fine-tuning LLMs, building custom embedding models, designing retrieval architectures that balance quality with sub-100ms latency constraints.
4.
Data richness
Access to one of the most comprehensive customer behavior datasets anywhere.
5.
Ownership
End-to-end — from research to production deployment to metric evaluation.
Key job responsibilities
1. Invent new approaches to contextual retrieval, relevance scoring, and LLM-based summarization.
2. Fine-tune and evaluate language models for domain-specific understanding.
3. Design experiments that measure real customer impact, not just benchmark scores.
4. Ship production systems and iterate based on live metrics.
5. Collaborate across teams — Alexa, Search, Recommendations — as a platform that powers them all.
6. Mentor team members and shape the technical direction of our roadmap.
Please visit https://www.amazon.science for more information.
A day in the life
You'll analyze large-scale behavioral data, design experiments, and build models that ship to production. You'll work closely with engineers to ensure your science translates into low-latency, high-reliability systems. You'll present findings to leadership and influence product strategy. Some weeks you'll be deep in model architecture; other weeks you'll be debugging a relevance gap in production. Every day, your work reaches real customers.
About the team
We're a small, high-impact team that values scientific rigor and engineering craft equally. The team values innovations and offers a safe place to try, fail and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. Our team offers creative space with entrepreneurial work environment focusing on customer obsession.
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