As the world works and lives faster, FIS is leading the way.  Our fintech solutions touch nearly every market, company and person on the planet. Our teams are inclusive and diverse. Our colleagues work together and celebrate together. If you want to advance the world of fintech, we’d like to ask you: Are you FIS?   

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 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.

About the role:

We are looking for a Senior 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.

Note: We have a hybrid work environment in our Seattle/Bellevue, office unless the role or business dictates otherwise.

What you will be doing:

• Understand business objectives, product requirements and develop ML algorithms that achieve them.
• Build Prototypes, and proof of concepts to determine feasibility, then drive data-based decisions.
• Run experiments to assess performance and improvements.
• Provide ideas and alternatives to drive a product/feature.
• Define data and feature validation strategies.
• Deploy models to production systems and operate them including monitoring and troubleshooting
• 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.
• Drive code reviews to ensure code quality, maintainability, and adherence to coding standards.
• 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.

What you will need:

• At a minimum, a Bachelor's in CS or equivalent education and either 3+ years of relevant professional experience or advanced degree such as a master’s or PhD.
• Experience leading projects from architectural design to production, while setting and maintaining high standards of technical excellence across your team. 
• Effective communication and collaboration skills, and a history of collaborating effectively with your team and cross-functional stakeholders. 
• Excellent communication and cross-functional collaboration skills to thrive in a fast-paced environment.
• Experience with data management, data, and build pipelines.
• Experience with building and deploying machine learning models.
• Experience with AWS, Snowflake, Databricks or similar technologies.

Added bonus if you have:

• Typical qualifications for the role are 7+ years of relevant professional experience or a combination of work experience and advanced education.
• Deep expertise in at least one area of Machine Learning and AI.
• Experience with financial services data sources.
• Experience with MLflow and Feast or other Feature Stores is helpful.
• Proficiency in modern development frameworks and languages. (e.g., Java, Python, Go). 
• Proven ability to self-direct your technical work and scope projects effectively.
• Experience leading and mentoring junior engineers.
• Excellent communication and collaboration skills to influence both technical and non-technical stakeholders.
• Experience with cloud platforms (AWS, Azure, GCP).
• Experience with version control systems (Git), and DevOps practices like continuous integration and continuous delivery (CI/CD).
• A strong understanding of security best practices for building enterprise applications.

What we offer you:

At FIS, we hire the best. In return, you receive exceptional benefits including:

• Opportunities to innovate in fintech.
• Tools for personal and professional growth.
• Inclusive and diverse work environment.
• Resources to invest in your community.
• Competitive salary and benefits.

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