MLOps Engineer

• Design, implement, and maintain scalable and reliable MLOps pipelines.
• Develop and deploy machine learning models using Python.
• Manage containerized applications using Kubernetes.
• Implement and manage CI/CD pipelines to automate the deployment process.
• Collaborate with data scientists and software engineers to integrate machine learning models into production environments.
• Utilize GitHub for version control and collaboration on code repositories.
• Leverage Argo for workflow automation and orchestration.
• Monitor and optimize the performance of deployed models and infrastructure.
• Troubleshoot and resolve issues related to model deployment and infrastructure.
• Stay up-to-date with the latest trends and best practices in MLOps and machine learning.

Required Qualifications:

• Bachelors degree in Computer Science, Engineering, or a related field.
• Proven experience as an MLOps Engineer or in a similar role.
• Proficiency in Python programming.
• Hands-on experience with Kubernetes for container orchestration.
• Strong understanding of code deployment and CI/CD processes.
• Experience with GitHub for version control.
• Familiarity with Argo for workflow automation.
• Excellent problem-solving skills and attention to detail.
• Strong communication and collaboration skills.

Preferred Qualifications:

• Masters degree in Computer Science, Engineering, or a related field.
• Experience with cloud platforms such as AWS, GCP, or Azure.
• Knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch).
• Experience with monitoring tools and practices for machine learning models.
• Understanding of data engineering and data pipeline concepts.,