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Machine Learning Engineer - Dubai, United Arab Emirates - KINGSTON STANLEY
Description
Model Deployment and Monitoring - Deploy machine learning models into production environments and implement robust monitoring solutions for performance and reliability.
Infrastructure Management - Work closely with DevOps and IT teams to maintain and enhance the infrastructure required for machine learning operations, leveraging cloud platforms and containerization technologies.
Automation - Develop and maintain automation scripts and tools for model deployment, scaling, and monitoring to streamline machine learning operations workflows.
Collaboration - Collaborate with data scientists, software engineers, and other stakeholders to understand model requirements, integration needs, and performance expectations.
Troubleshooting - Investigate and resolve issues related to machine learning model deployment, performance, and scalability in a timely manner.
Security and Compliance - Ensure machine learning operations adhere to security and compliance standards, implementing best practices for data privacy and model governance.
Skills & Background
Experience in deploying and maintaining machine learning models in production environments .
Proficiency in cloud platforms
Strong programming skills in languages Python
Experience with relevant frameworks (e.g., TensorFlow, PyTorch).
Familiarity with containerization technologies (Docker, Kubernetes).
Solid understanding of DevOps practices and tools.
Experience with continuous integration and continuous deployment (CI/CD) pipelines.
Knowledge of machine learning model serving platforms.