ML Ops Engineer

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📅  Posted 18 days ago 📍 India
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Job Description

Enable Data Incorporated is a leading provider of advanced application, data, and cloud engineering services focused on offering modern solutions that help customers drive increased value across their business ecosystem. We are currently seeking a Machine Learning Ops Engineer to join our team. This exciting position will be responsible for using machine learning technologies to help our clients build highly-scalable and sophisticated applications.


  • Design and implement cloud solutions, build MLOps on Azure cloud
  • Build CI/CD pipelines orchestration by Azure devops or similar tools
  • Data science model review, code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality
  • Data science models testing, validation and tests automation
  • Communicate with a team of data scientists, data engineers and architect, document the processes
  • Deep quantitative/programming background with a degree (Bachelor’s, Master’s, or Ph.D.) in a highly analytical discipline, like Statistics, Economics, Computer Science, Mathematics, Operations Research, etc.
  • Total of 3-6 years of experience in managing machine learning projects end-to-end, with the last 18 months focused on MLOps.
  • Monitoring Build & Production systems using automated monitoring and alarm tools.
  • Knowledge of machine learning frameworks: TensorFlow, PyTorchKerasScikit-Learn.
  • Experience with MLOps tools such as ModelDB, Kubeflow, Pachyderm, and Data Version Control (DVC).
  • Experience in supporting model builds and model deployment for IDE-based models and autoML tools, experiment tracking, model management, version tracking & model training (, model hyperparameter optimization, model evaluation, and explainability (SHAPTensorboard).
  • Experience in Databricks Lakehouse and Unity Catalog
  • Ability to understand tools used by data scientist and experience with software development and test automation