Description

You will operationalize machine learning models by building and managing a production-ready MLOps framework.

Responsibilities

• Design and implement production-ready model repositories using infrastructure as code principles.
• Develop and maintain CI/CD pipelines for seamless model deployment and updates.
• Customize and optimize ML pipelines within a Databricks environment.
• Manage model governance and compliance using Databricks Model Registry and MLflow.
• Collaborate with data scientists and engineers to optimize model performance and resolve operational challenges.

Required Skills

• 5+ years of experience in MLOps principles and best practices.
• Proficiency in Python and libraries including scikit-learn, TensorFlow, and PyTorch.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Hands-on experience with containerization using Docker and Kubernetes.
• Solid understanding of CI/CD pipelines and tools like Jenkins or GitLab CI/CD.
• Experience with version control systems using Git.
• Strong understanding of data engineering principles.
• Experience working with Databricks and MLflow.

Preferred Skills

• Experience with infrastructure as code tools such as Terraform or Ansible.
• Knowledge of cloud-native technologies and serverless computing.
• Experience with data governance and compliance regulations.

Key Skills

Education

Any Graduate