Senior Applied Scientist, FinTelligence

Amazon Inc.; Seattle (WA); Hybrid; USD 136,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC is seeking a Senior Applied Scientist to lead the development of generative AI applications for finance, tackling problems at the intersection of LLMs, multi-agent systems, and real-world operations.

You will design production-grade models, work across the full stack from architecture to deployment, and collaborate with finance, science, and engineering teams to impact thousands of professionals daily.

Qualifications

• PhD or Master’s degree with at least 6 years of applied research experience.
• 3+ years building ML models for business applications.
• Experience with neural deep learning methods.
• Proficiency in Java, C++, or Python.

Responsibilities

• Building AI systems that finance teams trust enough to rely on without manual review.
• Designing agents that learn from user corrections and improve with each interaction.
• Solving inference at massive scale using tiered model architectures and small language models.
• Developing evaluation frameworks that catch quality regressions before customers.

Skills

Machine learning

Deep learning

Java

C++

Python

Applied research

Education

PhD

Master's degree

Tools

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Hadoop

Spark

Job description

Job ID: 10399493 | Amazon.com Services LLC

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 job responsibilities

What You’ll Work On

• 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

Who Thrives Here

• 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.

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.

Work/Life Balance

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. When we feel supported in the workplace and at home, there's nothing we can’t achieve.

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.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. 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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 listed below. 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&D 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 https://amazon.jobs/en/benefits.

USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Veterans, military spouses, and people with disabilities are encouraged to apply.