AI ML Operations

December 6

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InfraCloud Technologies

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Cloud Native Applications • Container Orchestration • Continuous Integration/Deployment • Infrastructure as code • Cloud - Public, Private, Hybrid

201 - 500 employees

🤖 Artificial Intelligence

☁️ SaaS

Description

• Support the development, deployment, and operationalization of AI-based models. • Responsible for migrating our AI-based application to a self-hosted model. • Ensure robust model integration and manage the lifecycle of machine learning models. • Design architecture for self-hosted AI models, on-premise or in the cloud. • Set up automated deployment pipelines for CI/CD of machine learning models. • Monitor model performance, identify improvement areas, and develop retraining strategies. • Integrate AI models with existing platforms and automate the end-to-end ML pipeline. • Document model architectures, processes, and provide technical support for model-related issues. • Ensure compliance with data privacy and security regulations in deployments.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field. • 3+ years of experience in MLOps, with a focus on machine learning model deployment and management. • Hands-on experience with both on-premise and cloud-based AI model deployment (AWS, GCP, Azure). • Experience with containerization technologies (Docker, Kubernetes) for model deployment and scaling. • Familiarity with continuous integration/continuous delivery (CI/CD) tools (e.g., Jenkins, GitLab CI, CircleCI). • Experience in monitoring tools (e.g., Prometheus, Grafana) and managing model performance at scale.