Model Deployment-Machine Learning Engineer
Company: Risk Management Solutions
Location: King of Prussia
Posted on: July 14, 2025
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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 , West New York , Model Deployment-Machine Learning Engineer, IT / Software / Systems , King of Prussia, New Jersey
