amazon

amazon

Posted via Amazon Jobs

Sr. Applied Scientist, International Emerging Stores Payments

Posted Aug 26, 2026

Role at a glance

Job function
AI & Data AI Research & Applied Science
Salary
$167.1K – $226.1K/yr
Location
Seattle, Washington, United States
Work arrangement
On-site
Employment
Full-time
Education
Master's, PhD

Spotted an issue?

We’ll check it against the original posting.

Log in to report

Qualifications

Required

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

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.

About the role

Original posting provided by amazon

View original
Embark on an exciting science journey with International Emerging Stores Payments as we apply LLM techniques to improve the customer experience across multiple countries where we operate in. You will impact 1/4 of the world's population.

Key job responsibilities
1. Translate ambiguous opportunities in to defined science problem statements
2. Evaluate and identify the right ML algorithm to solve for the problems.
3. Identify and build the right features for the Models
4. Partner with IML team in applying GenAI development strategies to accelerate model development
5. Publish papers to internal and external conferences.

Basic Qualifications

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

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.

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, Seattle - 167,100.00 - 226,100.00 USD annually
amazon

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.