Job Description

Role & responsibilities Develop MLOps pipelines for AI/ML model training, validation, and deployment. Automate data ingestion, preprocessing, and feature engineering workflows. Optimize model training and inference performance for scalability and efficiency. Manage CI/CD pipelines for ML models using tools like Jenkins, CI/CD. Deploy models using cloud-based (AWS, Azure, GCP) and on-prem solutions (Docker, Kubernetes). Monitor ML models in production to ensure performance, reliability, and drift detection. Implement robust logging, version control, and rollback strategies for ML models. Work closely with data scientists, AI engineers, and Dev Ops teams to improve AI system integration. Ensure compliance with data security, governance, and model explain-ability best practices. Preferred candidate profile Perks and benefits