Machine Learning Engineer for Financial Technology

24 hours ago


Pasco, Washington, United States FIS Full time
Job Description

We are seeking a highly skilled Machine Learning Engineer for Financial Technology to join our team at FIS. As a leading fintech solutions provider, we touch nearly every market, company, and person on the planet. Our Fraud Intelligence team is on the cutting edge of data science and machine learning technology that detects and prevents fraud on a global scale.

The ideal candidate will have experience leading projects from architectural design to production, while setting and maintaining high standards of technical excellence across their team. They should possess excellent communication and collaboration skills to thrive in a fast-paced environment and be proficient in modern development frameworks and languages such as Java, Python, or Go.

The successful candidate will work closely with data scientists to develop and test machine learning models, drive code reviews to ensure code quality, maintainability, and adherence to coding standards, and provide live on-call support by participating in the team on-call rotation and owning production issues from root cause analysis to resolution to future prevention.

This is a full-time position with a salary range of $189,100 - $317,690 per year. The exact starting pay will depend on factors such as job-related skills, experience, and relevant education or training. If you are passionate about fintech and have a strong background in machine learning, we encourage you to apply.

About the Team:

FIS technology processes more than $40 Trillion per year and enables 95% of the world's leading banks. Our Fraud Intelligence team is committed to providing our employees with an exciting career opportunity and competitive compensation. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics.

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