Description:

Design, develop, and implement MLOps pipelines for continuous deployment and integration of machine learning models.
Collaborate with data scientists and engineers to optimize pipeline processes and automate training, testing, and deployment.
Monitor and maintain model pipelines for performance, accuracy, and reliability.
Ensure compliance with security and data privacy standards in MLOps activities.

Requirements:

3-5 years of experience in MLOps, DevOps, or a related field.
Bachelor’s degree in Computer Science, Data Science, or a related field.
Strong understanding of machine learning principles and model lifecycle management.
Proficiency in Python and experience with machine learning frameworks like TensorFlow or PyTorch.
Experience with cloud platforms (AWS, Azure, Google Cloud) and their machine learning services.
Familiarity with containerization tools (Kubernetes, Docker) and CI/CD pipelines.
Strong problem-solving skills and ability to troubleshoot complex issues.
Experience with monitoring tools for model performance in production.

Skills

Benefits