Develop, test, and evaluate ML and DL models guided by hypotheses and experimentation;
Plan, execute, and measure experiments in a structured manner;
Define performance, robustness, reliability, and model impact metrics;
Ensure explainability, traceability, and bias mitigation;
Support the transition from traditional solutions to AI-based approaches;
Work collaboratively across data, architecture, and governance domains;
Contribute to the definition and adoption of MLOps practices and responsible AI;
Produce technical documentation and methodological reports.

Bachelor's degree in Computer Science, Information Systems, IT Management or related fields (Engineering, Mathematics, Statistics, or similar).
Minimum of 5 years of experience in developing, implementing, and applying Artificial Intelligence solutions.
Knowledge of Machine Learning, Deep Learning, and applied statistical methods.
Experience with model evaluation, validation, and explainability.
Knowledge of MLOps and model lifecycle management.
Practice aligned with principles of ethics, governance, and responsible AI use.
Postgraduate degree in Data, Artificial Intelligence, Machine Learning or related areas (preferred).
Certifications in AI, Data, or Cloud (preferred).

Systems Architect – AI Specialist

Key skills