Join a pioneering team building cutting-edge machine learning applications that process and analyze billions of dollars in daily transactions using the latest technologies. This role offers a unique opportunity to make a significant financial impact, measured in millions of dollars saved. Our Finance Technology group is dedicated to advancing machine learning solutions for financial processes across Amazon.

We develop sophisticated systems for transaction scrutiny, employing advanced techniques such as forecasting, classification, and anomaly detection. Current initiatives focus on identifying data anomalies and optimizing cash levels for accounts, leveraging the newest tools like Generative AI and Large Language Models.

Participate comprehensively in the software development lifecycle, from initial customer collaboration on design to implementing scalable and extensible solutions. You will have the chance to apply machine learning techniques to detect fraudulent transactions and vendors, contributing directly to Amazon's business security daily.

Engage with machine learning scientists, fellow software engineers, and business groups across Amazon Finance Operations. Work with terabytes of data to develop robust machine learning pipelines processing billions of dollars in transaction value. Direct customer interaction is key, ensuring alignment with needs and incorporating feedback. Our team encourages innovation, providing opportunities to test new ideas in real-world financial environments.

A minimum of 3 years of professional software development experience, excluding internships, is required. Additionally, 2+ years of experience in designing or architecting new and existing systems, including familiarity with design patterns, reliability, and scaling, is essential. Proficiency in at least one software programming language is mandatory.

Preferred qualifications include 3+ years of experience across the full software development life cycle, encompassing coding standards, code reviews, source control, build processes, testing, and operations. A Bachelor's degree in Computer Science or a related field is advantageous, as is experience in machine learning, data mining, information retrieval, statistics, or natural language processing. Experience operating highly available, distributed systems for data extraction, ingestion, and processing of large datasets, or in development or technical support, is highly valued.