Moody's

MLOps Engineer

Moody's

full-time

Posted on:

Location Type: Remote

Location: United States

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Tech Stack

AWSCloudDockerKubernetesPythonSQL

About the role

  • 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

Requirements

  • 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
Benefits
  • Flexible work environment
  • Allow remote work depending on one’s personal choice
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningCI/CDPythonSQLDockerKubernetesML pipelinesmodel performance benchmarkingmonitoringorchestration
Soft Skills
communicationcollaborationstakeholder managementproblem-solvingattention to detail