Moody's CorporationRemote
Associate Director - Machine Learning Engineer
United States
Full Time
3 hours ago
$140,000 - $203,000 USD
H1B Sponsor Likely
Key skills
End-to-end data sciencePythonCloud platformsInfrastructure as CodeContainerization technologiesDatabasesdata processingMachine LearningAnalytical skillsAIMLDatabricksAWSAzureGCPTerraformKubernetesDockerCommunicationCollaboration
About this role
Moody's Corporation is a global leader in ratings and integrated risk assessment, transforming how the world sees risk through advanced AI solutions. They are seeking an Associate Director - Machine Learning Engineer to develop, implement, and deploy production-grade machine learning solutions, ensuring scalability and reliability in collaboration with cross-functional teams.
Responsibilities:
- Develop, implement, and deploy production-grade machine learning solutions and systems
- Develop, implement, and deploy machine learning solutions in production environments
- Design and implement software architecture for machine learning systems
- Collaborate with cross-functional teams to understand business requirements and design scalable and efficient solutions
- Ensure the scalability, reliability, and performance of ML engineering solutions
- Collaborate with data engineers and data scientists to integrate models into end-to-end data pipelines, services, and applications
Requirements:
- Experience working on end-to-end data science projects is required to understand and contribute to the full model lifecycle, from development to production
- Solid software development experience in at least one object-oriented language (Python preferred) is essential for building robust, production-grade ML systems
- Hands-on experience with cloud platforms (AWS, GCP, or Azure) is required to design, deploy, and manage scalable ML infrastructure
- Experience with Infrastructure as Code (e.g., Terraform) is necessary for creating automated, repeatable, and maintainable deployments
- Proficiency with containerization technologies (e.g., Docker, Kubernetes) is required for packaging, deploying, and orchestrating ML applications
- Experience working with databases and data processing tools like Databricks is necessary to build and manage data pipelines for ML models
- Strong problem-solving and analytical skills are essential for troubleshooting complex systems and designing effective solutions
- Excellent communication skills are required to collaborate effectively with cross-functional teams and translate business needs into technical solutions
- Bachelor's or higher degree in Computer Science, Machine Learning, or a related field