Description

You will manage the deployment, monitoring, and scaling of machine learning and deep learning models in production environments.

Responsibilities

• Build and maintain end-to-end MLOps pipelines, including CI/CD, for production-level projects at scale.
• Design and implement model monitoring pipelines to detect data drift, concept drift, and model drift.
• Develop and standardize MLOps frameworks using PySpark and Python.
• Troubleshoot ML pipelines in production and manage existing ML solutions at scale.
• Collaborate with data science and infrastructure teams to optimize AI/ML solution designs.

Required Skills

• 5+ years of experience in machine learning operations or related roles.
• Hands-on experience with cloud platforms such as Azure, AWS, or GCP.
• Proficiency in Python and PySpark for framework development.
• Proven track record of deploying and monitoring ML/DL models in production.
• Experience building scalable CI/CD pipelines for machine learning.
• Deep understanding of model monitoring techniques for drift detection.
• Knowledge of Responsible AI principles.
• Strong ability to lead teams and articulate technical concepts to stakeholders.

Preferred Skills

• Experience with large-scale distributed systems.

Key Skills

Education

Any Gradute