Intetics is seeking an experienced AI/ML Engineer to join our team. You will design, develop, deploy, and maintain production-ready machine learning solutions that support predictive analytics, forecasting, and AI-driven decision-making. In this role you will work with modern Azure technologies, enterprise data platforms, and MLOps practices to deliver scalable, reliable, and business-focused AI applications. Responsibilities include designing, developing, and deploying ML models; building predictive, forecasting, and probabilistic models for business use cases; performing feature engineering, data preparation, and model validation; monitoring model performance and ensuring reproducibility. You will integrate ML solutions with enterprise data platforms and BI applications; implement MLOps practices, automated testing, and deployment pipelines; and collaborate with cross-functional teams to deliver AI-driven business solutions. Requirements include strong Python programming skills for ML development; experience deploying ML models into production environments; experience with forecasting, predictive analytics, or probabilistic modeling; knowledge of feature engineering, model validation, and performance monitoring; experience with MLOps practices and automated deployment; and an understanding of explainable and responsible AI principles. Experience integrating ML solutions with enterprise data platforms is preferred. Nice to Have: experience with Monte Carlo simulations or other stochastic methods; experience with Azure Machine Learning, Microsoft Fabric Data Science, or MLf

Intetics is seeking an experienced AI/ML Engineer to join our team. You will design, develop, deploy, and maintain production-ready machine learning solutions that support predictive analytics, forecasting, and AI-driven decision-making. In this role you will work with modern Azure technologies, enterprise data platforms, and MLOps practices to deliver scalable, reliable, and business-focused AI applications. Responsibilities include designing, developing, and deploying ML models; building predictive, forecasting, and probabilistic models for business use cases; performing feature engineering, data preparation, and model validation; monitoring model performance and ensuring reproducibility. You will integrate ML solutions with enterprise data platforms and BI applications; implement MLOps practices, automated testing, and deployment pipelines; and collaborate with cross-functional teams to deliver AI-driven business solutions. Requirements include strong Python programming skills for ML development; experience deploying ML models into production environments; experience with forecasting, predictive analytics, or probabilistic modeling; knowledge of feature engineering, model validation, and performance monitoring; experience with MLOps practices and automated deployment; and an understanding of explainable and responsible AI principles. Experience integrating ML solutions with enterprise data platforms is preferred. Nice to Have: experience with Monte Carlo simulations or other stochastic methods; experience with Azure Machine Learning, Microsoft Fabric Data Science, or MLf