AI Engineering

• Assist in defining and developing AI systems.
• Analyze and evaluate AI techniques and technologies.
• Integrate and deploy AI solutions into existing systems.
• Manage data collection, preprocessing, and quality assurance for AI model training.
• Support verification and validation processes for AI systems.
• Train AI models and evaluate their performance, fine-tuning as necessary.
• Monitor AI system performance and implement necessary adjustments.
• Contribute to the establishment of AI development standards and knowledge dissemination.

Digital Innovation Engineering

• Identify and implement innovative ideas for shared platform services and tools.
• Evaluate AI techniques, frameworks, and optimization methods.
• Develop information factory environments and support their operations.
• Contribute to ESA's technology programs related to information factory development.
• Utilize innovative data access and analytics environments leveraging HPC infrastructures.

Data Science Engineering

• Define requirements for data-driven solutions with stakeholders.
• Gather, clean, and transform data from various sources, ensuring quality and consistency.
• Conduct exploratory data analysis to identify patterns and insights.
• Build predictive models and validate their performance.
• Implement machine learning algorithms for automated decision-making processes.
• Create visual data representations for effective communication of insights.
• Support technology development for ESA's data science programs.