MLOps Engineer (LLM MLOps)

Experience-4+yrs Key Responsibilities - Model Deployment using Docker and Kubernetes.

• Design, build, and maintain CI/CD pipelines for ML workflows.
• Monitor model drift, latency, and performance metrics.
• Manage cloud infrastructure across AWS, Azure, or GCP.
• Collaborate with Data Scientists to optimise model performance and scalability.

Required Skills - Strong proficiency in Python and Shell Scripting.

• Hands-on experience with Docker, Kubernetes, and CI/CD tools.
• Experience with TensorFlow, PyTorch, and Scikit-Learn.
• Knowledge of MLflow and Weights & Biases.
• Exposure to AWS SageMaker, Azure Machine Learning, or GCP Vertex AI.
• Good understanding of MLOps, DevOps, and ML deployment best practices.