Machine Learning Engineer

Your tasks

• 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.

Requirements

• 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.