Mlops Engineer Tamil Nadu (India)

Role Overview We are looking for a Machine Learning Engineer with hands-on experience in end-to-end model lifecycle management, production deployment, and LLM observability. The role focuses on building reliable ML systems, implementing monitoring and alerting, and troubleshooting production issues at scale, primarily on Azure cloud. Key Responsibilities Manage end-to-end ML model lifecycle and production deployments. Build monitoring, alerting, and LLM observability systems. Troubleshoot and debug production issues. Implement model governance, performance monitoring, and automated pipelines. Collaborate across teams to deliver scalable ML solutions. Requirements Solid experience in ML engineering, MLOps, and production systems. Hands-on with Python, TensorFlow/PyTorch. Azure (must-have) + one observability tool (e.g., Datadog, Grafana). Expertise in model monitoring, deployment, and debugging. Understanding of LLM observability and ML pipelines. Role Overview We are looking for a Machine Learning Engineer with hands-on experience in end-to-end model lifecycle management, production deployment, and LLM observability. The role focuses on building reliable ML systems, implementing monitoring and alerting, and troubleshooting production issues at scale, primarily on Azure cloud. Key Responsibilities Manage end-to-end ML model lifecycle and production deployments. Build monitoring, alerting, and LLM observability systems. Troubleshoot and debug production issues. Implement model governance, performance monitoring, and automated pipelines. Collaborate across teams to deliver scalable ML solutions. Requirements Solid experience in ML engineering, MLOps, and production systems. Hands-on with Python, TensorFlow/PyTorch. Azure (must-have) + one observability tool (e.g., Datadog, Grafana). Expertise in model monitoring, deployment, and debugging. Understanding of LLM observability and ML pipelines.