Applied Scientist II, IESP Digital Payments

Do you like working on projects that are highly visible and are tied closely to Amazon’s growth? Are you seeking an environment where you can drive innovation leveraging the scalability and innovation with Amazon's AWS cloud services? The Amazon IESP Digital Payments & Emerging Team is hiring Applied Scientists to work in our Machine Learning team in São Paulo, Brazil. The Payments team designs and builds scalable payment systems that power Amazon's checkout and financial services across emerging countries (Brazil, Mexico, Australia, Singapore, and more). We tackle complex challenges in payment orchestration, fraud detection, and regional payment method integration to drive conversion and deliver seamless experiences at scale.

Key job responsibilities
About you
You want to make changes that help millions of customers. You don’t want to make something 10% better as a part of an enormous team. Rather, you want to innovate with a small community of passionate peers. You have experience in analytics, machine learning, LLMs and Agentic AI, and a desire to learn more about these subjects. You want a trusted role in strategy and product design. You put the customer first in your thinking. You have great problem solving skills. You research the latest data technologies and use them to help you innovate and keep costs low. You have great judgment and communication skills, and a history of delivering results.
Your Responsibilities
- Define and own complex machine learning solutions in the consumer space, including targeting, measurement, creative optimization, and multivariate testing.
- Design, implement, and evolve Agentic AI systems that can autonomously perceive their environment, reason about context, and take actions across business workflows—while ensuring human-in-the-loop oversight for high-stakes decisions.
- Influence the broader team's approach to integrating machine learning into business workflows.
- Advise leadership, both tech and non-tech.
- Support technical trade-offs between short-term needs and long-term goals.

Basic Qualifications

- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

- Experience using Unix/Linux
- Experience in professional software development
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience

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