Senior Applied Scientist, Selling Partner Support Engagement

01 ott - Italia
Amazon

Job ID: 10442696 | Amazon.com Services LLC
Amazon's Selling Partner Support handles tens of millions of contacts annually worldwide. The Titans Science team is transforming this experience by building AI agents that autonomously resolve seller issues, learn from every interaction, and continuously improve with minimal human intervention. These agents reason, remember, and adapt — from understanding the seller's context and selecting the right solution, to routing contacts optimally, automating resolution end-to-end, and augmenting associates with AI when human judgment is needed. We do this in deep partnership with multiple engineering and product partners.
We are looking for a Senior Applied Scientist who wants to work at the intersection of reinforcement learning, agentic architectures, and large-scale production systems. You will be directly connected to the problems sellers face every day, translating real customer pain into science solutions that operate at massive scale.



You will frame ambiguous business challenges as tractable ML problems to shipping systems that measurably improve millions of seller interactions.
Key job responsibilities
- Own end-to-end research and development of RL-based agent improvement systems — from problem formulation through production deployment and impact measurement.
- Design novel approaches to preference learning, reward modeling, and policy optimization in the context of conversational agents operating over real-world tools and APIs.
- Build and maintain evaluation frameworks that measure agent quality across multiple dimensions: helpfulness, correctness, safety, and alignment with operational standards.
- Collaborate with a team of scientists that work on forefront of Natural Language Understanding, Optimization, Machine Learning and Statistics
- Partner with 10+ engineering teams to deploy models into production systems serving sellers worldwide.
- Publish research at top venues (NeurIPS, ICML, EMNLP, AMLC) — the complexity

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