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MLOps Engineer
3 months ago
Azure ML and related Azure technologies
Strong programming skills in languages such as Python, Java, or Scala
Responsibilities:
• Design, implement, and maintain end-to-end machine learning pipelines for model training, validation, and deployment.
• Collaborate with data scientists, software engineers, and DevOps engineers to integrate machine learning models into production systems.
• Develop automation tools and frameworks to streamline the machine learning workflow, including data preprocessing, feature engineering, model training, and evaluation.
• Optimize model performance and scalability by leveraging cloud computing resources and distributed computing techniques.
• Implement monitoring and logging solutions to track model performance, data quality, and system health in production.
• Manage model versioning, experimentation, and reproducibility using version control systems and experiment tracking tools.
• Stay up to date with the latest trends and technologies in machine learning, cloud computing, and software engineering, and incorporate them into the MLOps workflow.
• Provide technical guidance and mentorship to junior team members on best practices for MLOps.
Qualifications:
• Strong programming skills in languages such as Python, Java, or Scala.
• Proven experience as an MLOps Engineer, specifically with Azure ML and related Azure technologies.
• Familiarity with containerization technologies such as Docker and orchestration tools like Kubernetes.
• Proficiency in automation tools like JIRA, Ansible, Jenkins, Docker compose, Artifactory, etc.
• Knowledge of DevOps practices and tools for continuous integration, continuous deployment (CI/CD), and infrastructure as code (IaC).
- Bachelor's degree or higher in computer science, engineering, mathematics, or related field.