AI Infrastructure Manager

Roles and Responsibilities

• Infrastructure Development : Design, implement, and manage containerized GPU deployments using Docker.
• Multi-modal Projects : Integrate and deploy machine learning models for audio, video, and image processing tasks.
• Framework Integration : Collaborate with data science teams to ensure seamless integration of TensorFlow, Keras, and other deep learning frameworks into production pipelines.
• Kubernetes Management : Optimize and manage Kubernetes clusters for scalable and efficient deployment.
• Model Optimization : Utilize ONNX and C-based deployments for optimized model execution and scalability.
• Model Monitoring : Monitor model performance, detect model drift, and ensure the robustness of deployed models in production environments.
• Pipeline Support : Provide support for end-to-end machine learning pipelines, from data ingestion to model deployment.
• Cross-functional Collaboration : Ensure effective communication with cross- functional teams to align on project goals and deliverables.

Skillset

Experience

Qualification

About Zzazz

Zzazz is pioneering the next global information economy by transforming how digital content is valued and experienced. Our advanced Economic AI quantifies the real-time value and price of content, turning it into dynamic assets that reshape industries worldwide. At Zzazz, you'll join a team of innovators pushing the boundaries of AI and economics to create meaningful impact on a global sca