Machine Learning Engineer

at  FIS Global

EDUCATION DESIRED :

Bachelor’s Degree

JOB DESCRIPTION

FIS technology processes more than $40 Trillion per year and enables 95% of the world’s leading banks. 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. As a Machine Learning Data Engineer, you will tackle challenges ranging from identity theft to credit card fraud, to money laundering, and more. The technology you build will protect individuals, businesses and financial institutions from fraudsters ranging from individuals up to multinational organized crime rings. The fraud prevention space is fast-paced and rapidly changing. You will work cross-discipline with data scientists, analytics, product, and more. Our ideal candidate not only brings technical skills to the table but has the appetite to dig into deeply complex problems, while learning new skills along the way. We are leading the way and leveraging our wealth of data to create best-in-class solutions.
We are looking for a Machine Learning Engineer to help us build a brand-new financial technology platform for the future. We look for people who operate like owners, who loves to learn, have grit, and operate with integrity and empathy. You’re encouraged to apply even if your experience doesn’t precisely match the job description. Your skills and passion will stand out — and set you apart. We welcome diverse perspectives and people who are not afraid to challenge assumptions.

EEOC STATEMENT

FIS is an equal opportunity employer. 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. The EEO is the Law poster is available here supplement document available here
For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

• Translate product requirements into clean, maintainable, scalable, and well documented code.
• Design, build, and manage the data pipelines and infrastructure that collect, store, and process large volumes of transactional and customer data from various sources.
• Develop, deploy, and scale machine learning models and applications in production and lower environments
• Ensure data quality, security and availability for the data, notebooks, models, experiments, and applications.
• Integrate ML models with the SaaS platform and other services and tools, such as the model registry, feature store, data lake, and event streams.
• Collaborate with data scientists to develop and test machine learning models.
• Monitor and optimize machine learning models in production.
• Stay up to date with the latest developments in machine learning and data management.
• Debug and troubleshoot software issues to ensure business continuity, and a high bar for end-user experience.
• Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards.
• Write unit & integration tests, implement observability, and comply with best practices for builds and deployment to ensure the quality and reliability of our platform.
• 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.
• Partner with cross-functional teams (engineering, product, design, security, compliance etc.) to bring ideas to life
• Build secure, robust, scalable, and performant systems for processing transactions and managing customer data.
• Estimate project timelines, ensuring that projects you own stay on track and escalating as needed.