Azure ML Engineer

3 weeks ago


India TapTalent Full time
Main Responsibilities

We are seeking a skilled Azure ML Engineer to join our team at TapTalent. As a key member of our MLOps team, you will be responsible for designing, developing, and implementing MLOps pipelines for the continuous deployment and integration of machine learning models.

Key Responsibilities:

  • Design and develop MLOps pipelines for machine learning model deployment and integration.
  • Collaborate with data scientists and engineers to understand model requirements and optimize deployment processes.
  • Run machine learning feature engineering tests and improve models based on those tests.
  • Automate training, testing, and deployment processes for machine learning models.
  • Monitor and maintain models in production to ensure optimal performance, accuracy, and reliability.
  • Implement best practices for version control, model reproducibility, and governance.
  • Optimize machine learning pipelines for scalability, efficiency, and cost-effectiveness.
  • Troubleshoot and resolve issues related to model deployment and performance.
  • Ensure compliance with security and data privacy standards in all MLOps activities.
  • Stay up-to-date with the latest MLOps tools, technologies, and trends.
  • Provide support and guidance to other team members on MLOps practices.

Requirements:

  • 3+ years of experience in Azure, Azure machine learning, MLOps, DevOps, or a related field.
  • Strong understanding of machine learning principles and model lifecycle management.
  • Proficiency in programming languages such as Python with hands-on experience in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
  • Experience with cloud platforms like Azure, AWS, or their respective machine learning services.
  • Familiarity with containerization and orchestration tools like Docker and Kubernetes.
  • Knowledge of CI/CD pipelines automation tools and version control systems like Git.
  • Strong problem-solving skills and ability to troubleshoot complex issues.
  • Experience with monitoring tools and practices for model performance in production.
  • Ability to work collaboratively in cross-functional teams.

Nice to Have:

  • Bachelor's degree in computer science, data science, or a related field.
  • Azure ML Studio, Data Bricks, Fabric.
  • Familiarity with agile software development lifecycle (SCRUM, Kanban, etc.).

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