AI / ML Engineer

Role overview AI and machine learning engineering role focused on taking practical AI systems from development into reliable production use. The scope includes document extraction, information retrieval, predictive models, and agentic systems designed with clear operational boundaries. Success is measured through dependable performance and accuracy rather than experimentation alone.

Responsibilities - Build and productionize systems for extracting structured information from documents. - Develop retrieval-based solutions that return relevant, useful information for downstream workflows. - Create predictive models and evaluate their accuracy against meaningful production requirements. - Design agents with explicit boundaries, appropriate controls, and behavior that can be measured in practice. - Improve the reliability and usefulness of AI systems as they move from prototypes into real-world operation.

Requirements - Experience building AI or machine learning systems intended for production deployment. - Ability to work across document processing, retrieval, prediction, and agent-based applications. - A measurement-driven approach to model quality, accuracy, and system behavior. - Practical judgment about where autonomous systems need constraints and clearly defined limits.