Nature of tasks:

• [Essential] Integration and maintenance of software applications or services in the field of Artificial Intelligence (AI) in different technologies such as Natural Language Processing (NLP), Machine Learning (ML), Information Extraction, Knowledge Graphs (KG) or Graph Data Science (GDS);

• [Essential] Market studies and technical evaluation of advanced commercial or open-source products or services in the above fields;

• Training of custom machine learning / deep learning models based on structured and unstructured data;

• [Essential] Prompt engineering on Large Language Models and validation of results with the business/policy officers.

• Selecting features, building and optimizing classifiers using machine learning techniques;

• [Essential] Interact with policy officers, data stewards and other stakeholders to understand business and data needs, turn them into use cases, prototypes or statements of work and eventually support the solution acceptance process;

• Define data controls and implement actions to ensure data quality, integrity and performance

• Data mining using state-of-the-art methods;

• [Essential] Design the IT architecture and hosting solutions and coordinate its implementation considering cloud technologies, containers, DevOps, master- and meta-data management concepts and security;

• Contributing to the analysis of data management vision, strategy and policy and derive the IT requirements;

Requirements

SPECIFIC EXPERTISE AND TECHNOLOGIES

• At least 8 years of specific expertise in: Practical knowledge of Perl, Python, Matlab, R and their NLP/ML libraries (SpaCy, NLTK, scikit-learn, pandas…).

• At least 8 years of specific expertise in: Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks. Excellent knowledge of Large Language Model prompt engineering.

• At least 5 years of specific expertise in: Excellent knowledge of data management and analytics, including data quality. Excellent knowledge of advanced data retrieval tools.

• At least 5 years of specific expertise in: Good knowledge of AWS, Azure or other cloud platforms.

• At least 5 years of specific expertise in: Good knowledge of machine learning systems lifecycle.

• At least 5 years of: Good knowledge of software development methodologies such as Agile or RUP.

• At least 7 years of specific expertise in: Practical knowledge of query languages, such as SQL, Hive, Pig, etc and with information extraction. Practical knowledge of Python.

• At least 5 years of specific expertise in: Knowledge of NoSQL databases, such as MongoDB, Cassandra, HBase, Neo4j, etc.

• At least 5 years of specific expertise in: Experience with data analytics over big datasets, non-structured databases as well as data lakes, including data visualisation tools (e.g. D3.js, knowledge graphs, etc.)

• At least 5 years of specific expertise in: Good knowledge of applied statistics, such as distributions, statistical testing, regression, etc.

CERTIFICATION AND/OR STANDARDS

Optional certifications:

• AWS Certified Machine Learning

• Microsoft Azure AI Engineer Associate SAS Certified Professional AI and Machine Learning Certification.

▪ During the performance of above listed tasks, external service provider may have an access to sensitive or secured data or to secured areas. The proposed candidate must be therefore security clearable (EU-27 security clearance).

▪ All non-EU external service providers, who may have access either to EC premises or to EC network, are subject of security screening by Commission’s security directorate (HR.DS) before specific contract signature to assess risks vis-à-vis Commission’s sensitive non-classified information.