IDS Software and Consulting is an entity dedicated to Public Management, committed to technological innovation and providing high-quality services in a humanized manner. Have you ever thought about the transformative impact your work can have? At IDS, impacting lives is not just an aspiration—it's a mission that becomes reality! **Description:** A qualified professional to lead strategic initiatives in Machine Learning and Artificial Intelligence. This person will be responsible for managing the entire lifecycle of ML/AI solutions—from conception and planning to deployment and operation in production environments. The role requires a solid technical foundation, analytical thinking, strong leadership skills, and the ability to turn complex challenges into scalable, high-impact solutions. They are also expected to act as a technical reference, promoting excellence, innovation, and alignment between technology and business. **Responsibilities:** * Technical leadership of Machine Learning and Artificial Intelligence projects with end\-to\-end involvement: problem definition, analysis, modeling, development, validation, deployment, and production maintenance. * Planning and management of projects, including scope definition, scheduling, resource allocation, delivery tracking, and risk mitigation. * Defining architectures and strategies for scalable, robust, and secure ML/IA solutions. * Coordinating multidisciplinary teams and providing technical guidance to engineers, data scientists, and developers. * Implementing best practices in machine learning engineering, including MLOps, model versioning, pipeline automation, and performance monitoring. * Continuous communication with technical and business stakeholders to align expectations, prioritize tasks, and report results. * Evaluating and recommending technologies, frameworks, and tools for AI and data projects. **Technical Requirements:** * Proven experience developing ML/AI solutions in production environments. * Proficiency in languages and tools such as Python, TensorFlow, PyTorch, Scikit\-learn, among others. * Advanced knowledge of supervised and unsupervised machine learning techniques, deep learning, NLP, generative models, and recommendation systems. * Experience with MLOps practices and tools such as MLflow, Airflow, Kubeflow, Docker, and CI/CD for ML. * Experience with cloud-based architectures (AWS, GCP, or Azure) and model deployment in scalable environments. * Knowledge of data engineering applied to ML, including data preparation, ingestion, and transformation. **Leadership and Management Requirements:** * Experience leading technical teams, including mentoring, code/model reviews, and promoting best development practices. * Ability to manage multiple projects simultaneously using agile methodologies (Scrum, Kanban, etc.). * Skill in aligning technical objectives with business goals, ensuring high-impact deliveries within established deadlines. * Clear and concise communication with both technical and non-technical stakeholders.