AI MLOps Lead - Generative AI

Responsibilities

• Design, build, and maintain scalable and robust infrastructure, platforms, and CI/CD pipelines specifically for the ML lifecycle (training, validation, deployment, monitoring, retraining)
• Champion the evaluation, selection, and adoption of cutting-edge MLOps tools, technologies, and best practices to enhance efficiency, reliability, and speed of deployment
• Act as the primary technical lead for AI/ML operational concerns, effectively communicating deployment status, model performance metrics, infrastructure needs, and risks to both technical and senior stakeholders
• Foster strong collaboration between Data Science, Software Engineering, DevOps, and Infrastructure teams to ensure seamless integration and operation of AI models

Job Offer

• The opportunity to play a pivotal role in shaping an AI-forward, data-driven culture in a dynamic and data-ready work environment

Requirements

• Master's degree or equivalent practical experience in Computer Science, Engineering, Statistics, or a related quantitative discipline
• Minimum of 8 years of combined experience in software engineering, DevOps, data engineering, or data science, with at least 5 years specifically focused on MLOps or building/managing ML systems in production
• Strong understanding of the end-to-end machine learning lifecycle and associated challenges in operationalisation

Job Offer

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• The opportunity to play a pivotal role in shaping an AI-forward, data-driven culture in a dynamic and data-ready work environment

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
• 3–5+ years as an MLOps Engineer with a strong focus on operationalising machine learning models
• Demonstrable experience in designing, building, and maintaining CI/CD pipelines for ML models
• Strong programming skills, particularly in Python
• Familiarity with ML libraries/frameworks such as PyTorch, TensorFlow, etc.