Moody's

DevOps Engineer

• Deployment and productionisation or machine learning model applications in production.
• Design and develop reusable Terraform and Ansible modules.
• Lead the team in various aspects around stability, application delivery, and availability.
• Maintain a strong security awareness through frequent assessments and software architecture design processes.
• Influence technology selection, software architecture design, security practices and implementation.

Senior DevOps Engineer

Machine Learning Engineer

• Work closely with the Data Science team and the Data Engineers and DevOps teams in order to deploy machine learning models
• 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

MLOps Engineer

Research Scientist

• Collaborate with colleagues on production systems and applications
• Design, experiment, and evaluate algorithms as well as models using PyTorch, scikit-learn, Tensorflow, HuggingFace
• Work on POCs and research prototypes
• Provide thought leadership in machine learning
• Represent Moody’s Analytics at scientific and industry conferences
• Lead collaboration with colleagues and academia to publish research findings in leading academic venues such as ACL, EMNLP, NAACL-HLT, AAAI, KDD, CIKM, SIGIR, ECIR

Senior DevOps Engineer

MLOps Engineer

Machine Learning Research Scientist