Azure ML Engineer
3 weeks ago
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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