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 a Senior 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
You're someone who cares as much about shipping as about research.
You've built models that run in production, not just in notebooks.
You're comfortable working across the full stack, from model architecture to deployment to measuring whether the customer's workflow actually changed.
You operate well in cross-functional settings where science, engineering, and business teams inform each other continuously.
You'd rather solve a hard real-world problem than optimize a benchmark.
Preferred
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Have publications at top-tier peer-reviewed conferences or journals