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- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field.
- 5+ years of experience in DevOps or MLOps roles.
- Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
- Proficiency in programming languages such as Python, R, or Java.
- Strong understanding of cloud platforms (AWS, Azure, or GCP) and their machine learning services.
- Experience with containerization technologies, particularly Docker, and orchestration tools like Kubernetes.
- Knowledge of CI/CD tools like Jenkins, GitLab CI/CD, or Azure DevOps.
- Familiarity with data pipeline tools and frameworks, such as Apache Airflow or Kubeflow.
- Strong problem-solving and analytical skills.
- Excellent communication and teamwork abilities.
- Design, implement, and manage MLOps pipelines for deploying and monitoring machine learning models.
- Collaborate with data scientists to understand model requirements and operationalize models into production environments.
- Automate model training, testing, and deployment processes through CI/CD principles.
- Monitor and evaluate model performance in production and implement solutions for improvement.
- Implement data versioning, model versioning, and tracking systems to ensure reproducibility.
- Ensure security and compliance in the deployment of machine learning models.
- Document processes and improve collaboration between teams for efficient workflows.
- Stay up-to-date with industry trends and technologies in MLOps and machine learning.
AWSDockerPythonApache AirflowGCPJavaJenkinsKubeflowKubernetesMachine LearningPyTorchAirflowAzureData scienceTensorflowAnalytical SkillsCollaborationCI/CDDevOpsCompliance
Posted 2024-11-21
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