Principal Data Platform & Machine Learning Engineer

We are assisting our client in hiring for a Principal Data Platform & Machine Learning Engineer.

Our client is an established SaaS company serving banks, credit unions, and fintechs. Their cloud-based platform helps financial institutions improve collections performance, deliver a better consumer experience, reduce operating costs, anticipate delinquencies, and make more informed credit decisions.

This is a hybrid position based in Malvern, Pennsylvania. Candidates should be local to the Greater Philadelphia region and able to work onsite several days each week.

As part of a significant investment in Data & AI, our client is expanding its engineering organization with two newly created Machine Learning positions. This role will define the technical foundation that powers the company’s next generation of predictive analytics and AI capabilities.

This is a highly hands-on Principal Engineering opportunity for someone who enjoys building platforms as much as building software. You’ll establish the architecture, data pipelines, APIs, engineering standards, and machine learning infrastructure that enable intelligent products to scale across the business.

You’ll work closely with Product, Engineering, and executive leadership while mentoring other engineers and helping shape the technical direction of the platform. This is an opportunity to influence architecture, modernize engineering practices, and build production AI capabilities that directly impact customers and the future of the business.

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
• 7+ years of experience building large-scale data platforms, cloud-native applications, or production machine learning systems.
• Strong Python and SQL development skills.
• Experience designing scalable data architectures, APIs, distributed data processing solutions, and machine learning platforms.
• Experience with Azure, Databricks, MLflow, CI/CD, infrastructure automation, and MLOps.
• Proven ability to establish engineering standards, technical direction, and software best practices while remaining highly hands-on.
• Experience mentoring engineers and collaborating across multiple technical disciplines., * Financial services, banking, lending, collections, credit risk, or fintech.
• Designing enterprise-scale data platforms and machine learning infrastructure.
• Building highly available, cloud-native SaaS applications.
• AI-assisted software development tools and modern engineering practices.
• Passion for solving complex technical challenges while helping other engineers succeed.