Description of the Tasks Following tasks will be performed by the external service provider: Design the IT architecture for solutions in the NLP / ML / AI fields, and implement PoCs such as in the ChatBot / RAG field; Analyse data assets & business processes; Analyse risk-level of existing LLMs implemented in few of EMPL IT systems; Industrialise PoCs once they have proven to bring value-added, in close collaboration with other engineers members of EMPL.A4; Train custom machine learning (e.g. RAG based) based on structured and unstructured data; Interact with the local data correspondent, the digital transformation officer, and other IT stakeholders; Process, cleanse, and verify the integrity of data used for analysis; Follow the progress of implementation of corporate AI initiatives @EC, and identify opportunities to leverage the use of them within DG EMPL; Contribute to the analysis of data management vision, strategy and policy and derive the IT requirements. Requirements: Excellent knowledge of Python Excellent knowledge of NLP/ML and common Python libraries (e.g.: PyTorch, SpaCy, NLTK, Scikit-learn, Pandas, Pydantic) Very good knowledge of package management (e.g.: Poetry, pip, Conda) Very good knowledge of OOP and functional programming Very good knowledge of Git Extensive knowledge of machine learning techniques and algorithms Extensive knowledge of neural networks and deep learning, with a focus on text processing models Very good knowledge of prompt engineering techniques Very good knowledge of models MLOps techniques (model testing/deployment/monitoring/versioning, experiment tracking) Very good knowledge of Data Management Good knowledge of statistical analysis, experimental design and large scale data processing Good knowledge of LLMs and Transformer architecture Good knowledge of RAG systems Good knowledge of Azure and/or AWS Good knowledge of Docker, Kubernetes and IaC (e.g.: knowledge of Bicep and/or Terraform will be considered a plus) Good knowledge of Linux Good knowledge of NoSQL databases (e.g.: MongoDB, ElasticSearch) Good knowledge of vector DB Good knowledge of query languages (e.g.: SQL, ES, QL) Good knowledge of agile software development methodologies Skills: Ability to participate in multilingual meetings Ability to understand, speak and write English, optionally French as an additional asset Excellent interpersonal and communication skills Ability to work in a team as well as autonomously Results-oriented mindset, focused on delivering Good applied statistics skills, such as distributions, statistical testing, regression, etc. Good scripting and programming skills Data-driven mindset Non-Technical Skills: Capability of integration in an international/multicultural environment, rapid self-starting capability and experience in working in a team Ability to participate in multilingual meetings Ability to work in multi-cultural environment, on multiple large projects Excellent Team Player Specific Expertise: Any experience in the field of RAG processing will be considered as an asset