We are assisting our client in hiring for a Senior 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 a 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 is focused on building the predictive intelligence that becomes part of the company's core SaaS platform.
This is a highly hands-on engineering opportunity for someone who enjoys solving real business problems with machine learning. You'll design, build, deploy, and continuously improve production models that help financial institutions better predict customer behavior, prioritize collections strategies, and improve lending outcomes.
Working alongside Product, Engineering, Data, and business leaders, you'll help transform large volumes of structured data into intelligent software capabilities that customers use every day. If you enjoy owning the entire machine learning lifecycle—from feature engineering and model development through deployment, monitoring, and optimization—this is an opportunity to make a measurable impact.
What We're Looking For
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical discipline.
- 3+ years of experience designing, developing, and deploying production machine learning solutions.
- Strong Python and SQL development skills.
- Experience building predictive models using structured data.
- Experience with feature engineering, model evaluation, deployment, and ongoing model monitoring.
- Experience working with cloud-based data platforms and modern machine learning frameworks.
- Familiarity with Azure, Databricks, MLflow, MLOps, or similar technologies.
- Experience collaborating with engineering, product, and business teams to deliver production-ready AI solutions.
Preferred Experience
- Financial services, banking, lending, collections, credit risk, or fintech.
- Building scalable data pipelines and production machine learning systems.
- AI-assisted software development tools and modern engineering practices.
- Passion for solving complex business problems through data and machine learning.