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.

Note: This position is based in the greater Seattle/Bellevue, WA area. We plan to bring the team together regularly for design, ideation, and connection building.

Job Description:

We are looking for talented Machine Learning Engineers to join our team. The ideal candidate will have experience in data management, building and deploying machine learning models, and managing the build pipelines.

Responsibilities:

• 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.

• Govern the data in the pipeline.

• Stay up-to-date with the latest developments in machine learning and data management.

Requirements:

• Bachelor's or Master's degree in Computer Science, Mathematics, Engineering or a related field.

• 7+ years of experience in engineering.

• 5+ years of experience in machine learning engineering.

• Experience with data management and data pipelines.

• Experience with building and deploying machine learning models.

• Experience with managing build pipelines.

• Strong programming skills in Python and Java.

• Strong problem-solving skills.

• Excellent communication and collaboration skills.

• Experience with financial services data sources.

• Experience with AWS, Snowflake, Databricks is required.

• Experience with MLflow and Feast or other Feature Stores is helpful.

• Typically requires seven or more years of experience.

If you are interested in joining this exciting new team, please visit the FIS careers page for more information.