MLOPs Engineer

10 - 16 years

25 - 40 Lacs

Posted:4 weeks ago| Platform: Naukri logo

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Work Mode

Hybrid

Job Type

Full Time

Job Description

Responsibilities

  • Develop and maintain CI/CD pipelines for machine learning models.
  • Automate model deployment, monitoring, and scaling processes.
  • Implement and manage version control for code, data, and models.
  • Ensure data quality, security, and compliance throughout the ML lifecycle.
  • Collaborate with data scientists, engineers, and other stakeholders.
  • Optimize infrastructure for ML workloads.
  • Troubleshoot and resolve issues in production ML systems.
  • Implement logging, monitoring, and alerting for ML pipelines.
  • Manage and optimize cloud resources for ML/AI workloads.
  • Facilitate knowledge sharing and best practices across teams.
  • Mentors peer developers on ML Ops and Dev Ops

Technical Competencies

  • Programming languages: Python or similar
  • DevOps tools: Docker, Kubernetes, Jenkins, GitLab CI, or Azure DevOps
  • Cloud platforms: AWS, Azure, or Google Cloud Platform (AWS preferred)
  • Infrastructure as Code: Terraform, Ansible, or CloudFormation
  • ML frameworks: TensorFlow, PyTorch, or scikit-learn
  • Big data technologies: Spark, Hadoop, or Kafka
  • Monitoring and logging: ELK stack or similar
  • Version control: Git
  • Database management: SQL and NoSQL databases
  • Data pipeline tools: Airflow, Kubeflow or similar
  • Containerization and orchestration
  • CI/CD methodologies and tools
  • Understanding of ML algorithms and model serving
  • Knowledge of data privacy and security best practices
  • Familiarity with MLOps principles and tools (e.g., MLflow, DVC)

General Competencies:

  • Advanced customer-focus skills.
  • Advanced oral and written communication skills.
  • Advanced interpersonal skills.
  • Advanced decision-making skills.
  • Advanced organization and prioritization skills.
  • Advanced meeting facilitation skills.
  • Advanced team-building skills.

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