09 Sep
|
Capabiliq
|
Mumbai
Job DescriptionExperience-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