Machine Learning Engineer

Moody’s is seeking a Machine Learning Engineer to help build practical, scalable machine learning and computer vision capabilities that improve product performance and deliver measurable value for clients. This onsite role in Golden, CO supports work that combines data-driven model development with responsible AI governance, helping translate advanced techniques into operational outcomes.

As part of the Machine Learning Technology team, you will contribute to core technology behind award-winning property intelligence solutions, using machine learning, geospatial imagery, and computer vision to measure and monitor the built environment.

What you’ll do

• Develop robust, scalable machine learning and computer vision solutions that enhance product capabilities and support client value.
• Collect, clean, preprocess, and analyze data to enable model development and maximize data value.
• Create visualizations and perform exploratory analysis to uncover patterns, trends, opportunities, and data quality issues.
• Train, evaluate, refine, and deploy machine learning models aligned to business objectives and product requirements.
• Design, implement, and automate large-scale training, integration, and evaluation pipelines.
• Collaborate with machine learning, software engineering, product development, sales, and cross-functional stakeholders to deliver solutions.
• Communicate technical findings and recommendations to technical and non-technical audiences through documentation and presentations.
• Design and execute experiments to validate assumptions, improve model performance, and support data-driven decisions.
• Ensure work follows governance, security, ethical AI, and responsible data use practices, including identifying and resolving operational inefficiencies.

Required qualifications

• Advanced degree in a Science, Technology, Engineering, or Mathematics field.
• Minimum two years of hands-on industry experience in machine learning, computer vision, data science, or a related field (typical).
• Expertise in Python and machine learning libraries including NumPy, Pandas, and PyTorch.
• Expertise in supervised and unsupervised machine learning algorithms and implementations, including advanced concepts such as active learning, computer vision, and deployments in complex environments.
• Deep expertise in artificial intelligence, including implementing advanced AI solutions to improve strategic transformation and operational efficiency, using AI tools to lead innovation initiatives, and demonstrating leadership managing AI-related risks and ethical governance.
• Ability to communicate effectively in written and verbal forms, including articulating business requirements and objectives to both technical and non-technical stakeholders.

Preferred experience

• Machine learning operations practices including continuous integration and continuous deployment pipelines, model monitoring, and model maintenance.
• Experience with modern machine learning tools and platforms such as Jupyter, Docker, Git, and cloud environments like Amazon Web Services or Google Cloud Platform.
• Experience building data tools for extract, transform, and load processes, extracting data from SQL and NoSQL databases, and performing advanced data analysis.
• Geographic information systems experience.

Tools and technologies

• Python, NumPy, Pandas, PyTorch
• Jupyter, Docker, Git
• Amazon Web Services, Google Cloud Platform
• SQL, NoSQL

Compensation and location

• Location: Golden, CO (onsite)
• Salary: USD 95,500 - 138,550 per year

Benefits

• Incentive compensation
• Medical, dental, and vision
• Parental leave
• Paid time off
• 401(k) plan with employee and company contribution opportunities
• Life insurance, disability insurance, and accident insurance
• Discounted employee stock purchase plan
• Tuition reimbursement

About the team

The Machine Learning Technology team provides the core technology behind award-winning property intelligence solutions. The team leverages machine learning, geospatial imagery, and computer vision to measure and monitor the built environment while delivering actionable insights to clients. Through this work, the team helps organizations understand how homes and workplaces can withstand evolving climate and economic risks, while advancing responsible AI adoption across products and solutions.