10 Sep
|
Capabiliq
|
Mumbai
Job Description
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. Positive understanding of MLOps, DevOps, and ML deployment best practices.
📌 MLOps Engineer (Mumbai)
🏢 Capabiliq
📍 Mumbai