MLOPS Engineer

Key Responsibilities Design and implement end-to-end ML pipelines from data ingestion to model deployment Build and manage CI/CD pipelines for ML models (training, testing, deployment) Automate model monitoring, retraining, and performance optimization Collaborate with Data Scientists and Data Engineers for productionizing ML models Ensure scalability, reliability, and security of ML systems Manage model versioning, experiment tracking, and lifecycle management Implement best practices for governance, compliance, and reproducibility Key Skills & Expertise Strong programming skills in Python Experience with ML frameworks : TensorFlow, PyTorch, Scikit-learn Hands-on experience with MLOps tools : MLflow, Kubeflow, Airflow, SageMaker, Azure ML Knowledge of CI/CD tools : c Experience with cloud platforms : AWS Strong understanding of data pipelines, ETL processes, and distributed systems