Role at a glance
- Salary
- $142.8K – $193.2K/yr
- Location
- Bellevue, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Education
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
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Role Summary
The Applied Scientist will develop generative AI applications for Amazon's FinTech organization, supporting finance workflows involving financial transactions, complex documents, and autonomous agents. The role focuses on deploying reliable AI systems across areas including contract intelligence, cash application, and financial data investigation.
What You'll Do
- Build AI systems that finance teams can rely on without manual review, with precision suitable for compliance requirements.
- Design agents that learn from user corrections and improve with each interaction.
- Solve inference at massive scale using tiered model architectures, intelligent routing, and small language models.
- Develop evaluation frameworks to catch quality regressions and gate model changes before production release.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Key job 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
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.
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
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 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 Qualifications
- 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
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 - 142,800.00 - 193,200.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.