About the job
At Amazon's FinTech organization, we are building AI systems that process hundreds of millions of financial transactions, turn complex documents into actionable intelligence, and power autonomous agents that learn from every customer interaction. We are looking for an Applied Scientist to lead the development of generative AI applications that change how finance teams work, tackling problems at the intersection of large language models, multi-agent systems, and real-world financial operations.
Responsibilities
- Building AI systems that finance teams trust enough to rely on without manual review, where precision isn't a nice-to-have, it's a compliance requirement
- Designing agents that learn from user corrections and get measurably better with every interaction, not just at the next model release
- Solving inference at massive scale using tiered model architectures, intelligent routing, and small language models that deliver production-grade accuracy at a fraction of frontier model cost
- Developing evaluation frameworks that catch quality regressions before customers do and gate every model change before it ships
Qualifications
Minimum
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in building machine learning models for business application
- Experience programming in Java, C++, Python or related language
- 3+ years of building models for business application experience
Preferred
- PhD in computer science, machine learning, engineering, or related fields
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Experience in patents or publications at top-tier peer-reviewed conferences or journals