AI Engineer

• Design, develop and deploy machine learning solutions and services
• Implement end-to-end machine learning pipelines from data ingestion to training and model serving
• Operationalize LLMs, embeddings, and multi-agent systems in real-world applications
• Manage the machine learning and model lifecycle (experimentation, registry, deployment)
• Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production
• Containerize applications using Docker and orchestrate them via Kubernetes
• Build and maintain CI/CD pipelines for ML models and LLM applications
• Collaborate with data scientists to refactor research code into production-ready Python code
• Monitor model performance, data drift, and performance in production
• Assess and integrate AI solutions ensuring optimal performance and relia...

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