Senior Applied Scientist, FinTelligence

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.

Key Responsibilities

• Building AI systems that finance teams trust enough to rely on without manual review, where precision is 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.

Who Thrives Here

• Someone who cares as much about shipping as about research.
• Has built models that run in production, not just in notebooks.
• Comfortable working across the full stack, from model architecture to deployment to measuring whether the customer’s workflow actually changed.
• Operates well in cross‑functional settings where science, engineering, and business teams inform each other continuously.
• Prefers solving a hard real‑world problem than optimizing a benchmark.

What makes this different: Your work ships to production and directly changes how thousands of finance professionals operate daily. The problems are genuinely hard—financial data is messy, regulated, high‑stakes, and operates at a scale where naive LLM approaches break down. You’ll work across multiple domains—from contract intelligence to cash application to financial data investigation—not a single narrow use case.

We value work‑life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture.

Basic Qualifications

• PhD or Master’s degree and 6+ years of applied research experience.
• 3+ years of building machine learning models for business application experience.
• Experience with neural deep learning methods and machine learning.
• Experience programming in Java, C++, Python or related language.

Preferred Qualifications

• 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.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is: USA, WA, Bellevue 167,100.00 – 226,100.00 USD annually. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&DD insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at