Applied Scientist II - AI for Global Payments & Inclusion

Amazon Science; Seattle (WA); Sur place; USD 143 000 - 193 000; Plein temps

Avantages offerts par ce poste

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Résumé du poste

Amazon Science's International and Emerging Stores Payments (IESP) team seeks an Applied Scientist II to design, build, and ship ML and generative-AI solutions that improve financial inclusion across global markets. You will work at the intersection of research and production, turning data into decision-ready insights and deploying models in live shopping traffic.

You will design and evaluate large-scale models, mentor teammates, and publish research or file patents as appropriate, contributing

Qualifications

• 3+ years of building models for business applications.
• PhD, or Master's + 4+ years in CS/CE/ML or related field.
• Experience programming in Python, Java, C or C++.
• Experience solving business problems with ML, data mining and statistics.

Responsabilités

• Design, develop, and evaluate ML models and deploy production-ready solutions to complex customer and business problems.
• Conduct rigorous scientific research: form hypotheses, run experiments, evaluate model performance, and iterate.
• Write clean, maintainable code that integrates into larger systems and meets high operational standards.
• Partner with engineering to take models to production and with scientists to solve shared problems.
• Contribute to team roadmaps and mentor peers; publish at peer-reviewed venues or file patents where appropriate.

Connaissances

Machine learning

Python

Java

C/C++

Data mining

Statistical algorithms

Formation

PhD in Computer Science

Master's in a quantitative field

Description du poste

Amazon Science's International and Emerging Stores Payments (IESP) team seeks an Applied Scientist II to design, build, and ship ML and generative-AI solutions that improve financial inclusion across global markets. You will work at the intersection of research and production, turning data into decision-ready insights and deploying models in live shopping traffic.

You will design and evaluate large-scale models, mentor teammates, and publish research or file patents as appropriate, contributing