AI Engineer

Responsibilities

• Ensure the development, operationalization, monitoring and optimization of the value chain of artificial intelligence models, especially those based on LLMs (Large Language Models);
• Optimize performance, cost, and latency of AI solutions in production;
• Ensure the proper functioning of machine learning models and the overall efficiency of the cloud platform used for the development of generative AI solutions;
• Ensure the performance, reliability, conversational quality, and observability of AI systems in production;
• Participate in the optimization of the LLMOps pipeline including training, fine-tuning, deployment and validation of models;
• Configure critical alerts and thresholds for application components and AI systems to detect anomalies, quality degradations, and model drift.

Requirements

• Hold a bachelor's degree in computer science, software engineering, artificial intelligence or a relevant discipline;
• Possess a minimum of eight (8) years of relevant experience, or an equivalent combination of education and experience;
• Demonstrate experience in building generative AI models and solutions;
• Possess knowledge of observability tools such as Dynatrace and Splunk;
• Have knowledge of LLMOps, MLOps practices and AI system monitoring;
• Proficiency in Python and SQL languages as well as data processing, NLP and machine learning libraries;
• Have knowledge of Git and MLOps best practices including ML Pipelines, CI/CD, and monitoring;
• Knowledge of machine learning and natural language processing.