Azure AI & Machine Learning Engineer

Who We Are

We operate beyond organizational silos, combining deep expertise in data engineering and AI-driven solutions to design and deliver scalable, user-centric applications and modern data architectures. We support a wide range of industries, including Automotive, Banking, Insurance, Telecommunications, E-commerce, and Public Services.

Who We Are

We operate beyond organizational silos, combining deep expertise in data engineering and AI-driven solutions to design and deliver scalable, user-centric applications and modern data architectures. We support a wide range of industries, including Automotive, Banking, Insurance, Telecommunications, E-commerce, and Public Services.

Our focus is on building robust, enterprise-grade data platforms and enabling advanced analytics and AI capabilities within the Microsoft ecosystem, including Azure, Microsoft Fabric, and the Power Platform. We specialize in designing secure, high-performance solutions that integrate data pipelines, AI models, and Generative AI use cases to deliver real business value.

What You’ll Be Doing

• Architect and deploy AI solutions using Microsoft Azure services


• Design end-to-end AI/ML architectures covering data ingestion, feature engineering, model training, deployment, and monitoring


• Implement MLOps practices, including CI/CD pipelines and operational monitoring


• Preprocess and analyze data to ensure high-quality inputs for AI and retrieval-based systems


• Create and manage vector indexes to support AI search and retrieval use cases


• Evaluate, select, and integrate appropriate ML frameworks, tools, and platforms


• Ensure AI solutions comply with security, cost, and performance standards

What You Bring Along

• Bachelor’s degree in Computer Science, Informatics, Engineering, or equivalent practical experience


• Minimum 5+ years of experience ML and AI-focused roles


• Strong experience designing and deploying AI/ML solutions on Microsoft Azure


• Solid understanding of end-to-end ML pipelines and MLOps concepts


• Hands-on experience with CI/CD pipelines and production monitoring for AI systems


• Expertise in data preprocessing, feature engineering, and data quality assurance


• Practical knowledge of vector databases, embeddings, and retrieval-based AI systems


• Experience evaluating and selecting ML frameworks and tooling based on use case needs


• Good awareness of security, cost optimization, and performance considerations in cloud-native AI solutions


• Excellent verbal and written communication skills in English