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MLOps Engineer

Job Description:

  • 2+ years relevant experience in developing continuous integration and deployment (CI/CD) pipelines (e.g. Jenkins, Github Actions) and bringing ML models to CI/CD pipelines. 
  • Proficient knowledge of git, Docker and containers, Kubernetes. 
  • Fluency in any of Infra as a code using tools like – Terraform/ Ansible/chef. 
  • Fluency in Python, Shell/ Bash or other common system maintenance and scripting languages. 
  • Good knowledge of Linux system administration.
  • E2E production experience with Azure ML, Azure ML Pipelines, Sagemaker, GCP AI Platform. 
  • Worked on Model Drift (Concept Drift, Data Drift preferable on Azure ML.) 
  • You will be part of a cross-functional team that builds and delivers production-ready data science projects. 
  • You will work with team members and stakeholders to creatively identify, design, and implement solutions that reduce operational burden, increase reliability and resiliency, ensure disaster recovery and business continuity, enable CI/CD, optimize ML and AI services, and maintain it all in infrastructure as code everything-in-version-control manner. 
  • Candidate should have prior experience in Design, build, test, and maintain machine learning infrastructure to empower data scientists to rapidly iterate on model development. 
  • Familiarity with Data, Feature and Pipeline Versioning of ML assets using tools like DVC/CML or similar. 
  • Familiarity with setting up model and experiment Versioning technologies like MLFLow/ Kubeflow/ AWS Sagemaker or similar. 
  • Familiarity with setting up Hyperparameter Tuning tools like optuna/ kubeflow/AWS Sagemaker or similar. 
  • Model Deployment and Monitoring using technologies like Hydrosphere/KubeFlow/ Seldon/ AWS Sagemaker or similar. 
  • Experience with Agile/Scrum software development methodologies.
Job Type: Full Time
Job Location: Indore/Madhya Pradesh

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