Job offer

We are seeking a candidate with expertise in Cognitive AI, Agents, and Human Interaction who combines technical skills in artificial intelligence engineering with an understanding of human factors, cognitive psychology, human-machine interaction, and the evaluation of people-centered intelligent systems. The role is focused on supporting the design, implementation, testing, and validation of cognitive AI solutions capable of interpreting language, processing context, reasoning about objectives, generating plans, interacting with humans, and supporting decision-making or automation tasks in the fields of security, robotics, cybersecurity, and defense., Implementation of cognitive AI modules Implement components for language understanding, intent classification, entity extraction, constraints, and context. Develop prototypes for generating structured specifications, plans, task trees, or conceptual behavior trees

Development of Agents and Interactive Systems Collaborate on the development of agents based on LLMs, RAG, embeddings, memory, tools, and decision flows. Implement human-machine interaction tests using text, voice, graphical interfaces, simulators, or robotic environments.

Cognitive, Behavioral, and Human Factors Modeling Define conceptual frameworks based on attention, memory, perception, decision-making, mental load, learning, and trust. Translate psychological and cognitive constructs into measurable variables applicable to AI systems.

Experimentation, Evaluation, and Data Analysis Conduct experiments to train, validate, and compare AI models. Prepare datasets, clean data, document preprocessing workflows, and ensure experimental traceability.

Generative AI, Multimodal Models, and Decision Support Systems Use LLM APIs and frameworks for generation, classification, extraction, reasoning, and evaluation tasks. Implement basic or intermediate workflows involving prompting, embeddings, RAG, vector stores, and response evaluation.

MLOps, Quality, Security, and Documentation Use Git, GitHub/GitLab, and best practices for collaborative development. Support reproducible pipelines using MLflow, DVC, Docker, notebooks, and basic CI/CD.

Technical Skills Programming: Python as the primary language; C++ is a plus. AI/ML Frameworks: PyTorch, TensorFlow, Hugging Face, scikit-learn. Data: Pandas, NumPy, visualization, notebooks, data cleaning, and analysis. Deep Learning Fundamentals: CNNs, RNNs/LSTMs, transformers, and basic generative models. Basic to intermediate knowledge of LLMs, embeddings, RAG, prompting, model APIs, and agents. Version control: Git, GitHub/GitLab. A plus: Docker, MLflow, DVC, CI/CD, ROS2, audio processing, computer vision, or simulators. Applied statistics, experimental design, and behavioral analysis.

Joining our team means working in a cutting-edge and unique environment that will allow you to participate in technological development and innovation, offering solutions adapted to current economic and social needs. If you consider yourself a strong team player who also has a high degree of autonomy, if you are capable of contributing solutions and ideas and are an analytical person, don't wait any longer. This is the project for you, and we want to meet you!, Master Degree or equivalent

Languages ENGLISH

Funditec (Technological Foundation) promotes applied R&D projects to address critical challenges in digital transformation and security. The Funditec Intelligence unit leads AI/ML-based initiatives aimed at achieving real impact in sectors such as cybersecurity, defense, and dual-use systems.