MLOps Engineer

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February 12

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Moody's

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Banking • Finance • Fintech

Moody's is a global provider of data and insights, specializing in credit ratings, research, and risk management. The company serves a diverse range of clients including banking institutions, corporations, the buy-side, insurance companies, and public sector organizations. Moody's offers solutions for risk management, financial analysis, and compliance, leveraging technology such as artificial intelligence to optimize decision-making and help clients navigate uncertainty in financial markets.

10,000+ employees

🏦 Banking

💸 Finance

💳 Fintech

📋 Description

• Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models. • Specifically execute continuous integration and continuous delivery (CI/CD) activities to release ML code and ML pipelines into a Production environment • Maintain the Machine Learning pipeline and make sure everything is running accurately and reliably • Liaise with senior stakeholders across the Data function and the wider business • Use industry best practices such as code reviews, pull requests, and peer testing to ensure high quality AI/ML deliverables • Build AI/ML model performance benchmarking, evaluation, monitoring capabilities and facilitates resolution of issues with the appropriate teams

🎯 Requirements

• Must Have: • Proven industry/commercial/research lab experience (2+ years) deploying machine learning models and maintaining ML pipelines, orchestration, deployment, monitoring, & support • Experience creating and maintaining deployment pipelines with CI/CD tools (2+ years) • Knowledge of cloud technologies (e.g. AWS) and Extensive Programming experience in Python & SQL • Experience in containerization and orchestration (such as Docker, Kubernetes) • Practical Knowledge of Machine Learning models in commercial settings • Good communication skills • Nice to Have: • Experience building batch and/or real-time data & ML pipelines • Familiarity with MLflow (or similar platforms like Kubeflow and other tools) • Promotes a practice of unifying system development (Dev) and system operations (Ops)