09 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 Tensor Flow, PyTorch, and Scikit-Learn.
Knowledge of MLflow and Weights & Biases.
Exposure to AWS Sage Maker, Azure Machine Learning, or GCP Vertex AI.
Valuable understanding of MLOps, Dev Ops, and ML deployment best practices.
📌 Mlops Engineer Llm Mlops Jaipur (India)
🏢 Capabiliq
📍 India