Our client is a leading Software, Information and Communication Technologies company, operates internationally (Athens, Brussels, Luxembourg, Copenhagen, Stockholm, London, Nicosia, Hong-Kong, Valetta, etc). They are a renowned supplier of IT services to government institutions, multinational corporations, public administrations and multinational companies, research and academic institutes.
Role Overview
Our client has a vacancy for an AI /NLP/ ML Expert fluent in English, to offer his/her services as an expert who will be based in Brussels, Belgium. The work will be carried out either on the company’s premises or on site at the customer premises. In the context of the first assignment, the successful candidate will be integrated in the Development team of the company that will closely cooperate with a major client’s IT team on site.
Job Type: Full-time | Permanent
Work Type: Onsite
Location: Brussels, Belgium
Requirements
Master’s degree in IT or relevant discipline, combined with minimum 17 years of relevant working experience in IT
Experience with data analytics over big datasets, non-structured databases as well as data lakes
Excellent knowledge of Python
Excellent knowledge of machine learning techniques and algorithms, such as SVM, Neural Network, and/or artificial intelligence frameworks
Excellent knowledge of Data Management
Good knowledge of AWS and/or Azure
Good knowledge of Linux
Good knowledge of natural language processing systems lifecycle and agile software development methodologies
Good knowledge of NoSQL databases, such as MongoDB
Good knowledge of graph DB and triples
Good knowledge of query languages, such as SQL, Hive, Pig, etc.
Knowledge of data visualisation tools, such as D3.js, GGplot, etc
Knowledge of R and its NLP/ML libraries is a plus (e.g.: SpaCy, NLTK, scikit-learn, pandas…)
Excellent command of the English language and good command of French would be an asset
Responsibilities
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 IT systems
Industrialise PoCs once they have proven to bring value-added, in close collaboration with other engineers
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, and identify opportunities to leverage the use of them
Contribute to the analysis of data management vision, strategy and policy and derive the IT requirements
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