08 Sep
|
Capabiliq
|
India
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
- Solid 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.
📌 MLOps Engineer (LLM MLOps) (India)
🏢 Capabiliq
📍 India