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MLops Engineer @ Capgemini

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 MLops Engineer

Job Description


 Your Role 
  • Design, implement, and maintain end-to-end ML pipelines for model training, evaluation, and deployment
  • Collaborate with data scientists and software engineers to operationalize ML models, serving frameworks (TensorFlow Serving, TorchServe) and experience with MLOps tools
  • Develop and maintain CI/CD pipelines for ML workflows
  • Implement monitoring and logging solutions for ML models, experience with ML model serving frameworks (TensorFlow Serving, TorchServe)
  • Optimize ML infrastructure for performance, scalability, and cost-efficiency
  •  Your Profile 
  • Strong programming skills in Python, with experience in ML frameworks; understanding of ML-specific testing and validation techniques
  • Expertise in containerization technologies (Docker) and orchestration platforms (Kubernetes), Knowledge of data versioning and model versioning techniques
  • Proficiency in cloud platform (AWS) and their ML-specific services
  • Strong understanding of DevOps practices and tools (GitLab, Artifactory, Gitflow etc.)
  • Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack) and knowledge of distributed training techniques
  •  What youll love about working here 
  • We recognise the significance of flexible work arrangements to provide support in hybrid mode, you will get an environment to maintain healthy work life balance
  • Our focus will be your career growth & professional development to support you in exploring the world of opportunities.
  • Equip yourself with valuable certifications & training programmes in the latest technologies such as MLOps, Machine Learning
  • Job Classification

    Industry: IT Services & Consulting
    Functional Area / Department: Engineering - Software & QA
    Role Category: Software Development
    Role: Search Engineer
    Employement Type: Full time

    Contact Details:

    Company: Capgemini
    Location(s): Hyderabad

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    Keyskills:   devops ml python cloud platform container orchestration artifactory kubernetes continuous integration openshift ci/cd docker ansible git java linux jenkins shell scripting prometheus maven microsoft azure amazon ec2 grafana gitlab terraform aws

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