Expert in AI/ NLP/ ML

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