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Model Deployment-Machine Learning Engineer

Company: Risk Management Solutions
Location: King of Prussia
Posted on: July 14, 2025

Job Description:

At Moodys, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies Required: • Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Physics, or another quantitative field with 3 years of industry experience. • Strong programming skills in Python or R. • Proficiency in Linux-based systems, including shell scripting and command-line tools. • Excellent communication skills in English (both written and verbal). Preferred: • Ph.D. in Computer Science, Software Engineering, Mathematics, Statistics, or Physics. • A strong public record of programming experience (e.g. active GitHub or open-source contributions). • Experience with containerization (Docker) and orchestration (Kubernetes). • Hands-on experience with AWS services including EC2, S3, and Lambda. • Familiarity with machine learning and statistical modeling, both in theory and application. Education Master’s degree in Computer Science, Software Engineering, Mathematics, Statistics, Physics, or another quantitative field Responsibilities We are seeking a highly skilled and motivated Model Deployment / Machine Learning Engineer to enhance our model deployment processes and infrastructure. The ideal candidate will have deep experience in implementing and maintaining computational models at scale, with proficiency in R, Python, Linux, and AWS. This role involves close collaboration with cross-functional teams to support the entire model lifecycle from development and deployment to long-term maintenance and optimization. • Collaborate with research teams to translate statistical and machine learning models into efficient, production-ready code. • Design, build, and maintain packages for deploying credit analytics and predictive models in production environments. • Support the end-to-end model lifecycle including testing, validation, monitoring, and continuous improvement. • Troubleshoot and resolve technical issues related to model performance and infrastructure. • Develop and maintain documentation for deployment processes and infrastructure components. • Work with cross-functional teams to ensure model implementations meet product requirements and performance standards. • Contribute to the advancement of best practices for model deployment and maintenance within the Credit COE. About the team The Credit Center of Excellence (COE) at Moody’s is dedicated to maintaining and enhancing our industry-leading credit analytics and predictive modelling capabilities. We work closely with various departments including product management, commercial strategy, and go-to-market leaders to ensure the delivery of high-quality credit risk assessments and solutions. This collaborative approach allows the COE to integrate seamlessly into Moody’s Analytics structure to support and grow our customers’ business operations and enhance their ability to navigate risk.

Keywords: Risk Management Solutions , Freeport , Model Deployment-Machine Learning Engineer, IT / Software / Systems , King of Prussia, New York


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