As the successful candidate, you will primarily contribute to a partnership project with BGL; BNP Paribas, one of the major banks in Luxembourg. The title of the project is “AI for AI” and it concerns the design of an AI ‘metamodel’ tool that will monitor and improve AI algorithms effectiveness and robustness, allowing their application to business-critical use cases at scale. The objective of this project is to develop automated means to continuously monitor the performance of AI models (including NLP models) developed by BGL BNP Paribas and to determine when and how to retrain these models in order to improve their performance. Achieving these objectives requires addressing crucial research challenges such as the definition of proper quality metrics across the bank’s use cases, the identification and explaination of the limitations and blanks spots of the models, and the design of sustainable improvement mechanisms
Requirements:
The candidate should possess an PhD degree (or equivalent) in computer science with strong skills in software engineering, programming, and artificial intelligence, as well as good knowledge of computer science in general. The ideal candidate should have some knowledge and/or experience in most of the following topics: Programming (Python is a must, Java is an asset); Data science, data engineering, data collection and storage; Artificial intelligence, machine learning; Natural Language Processing is a plus (but not mandatory)
Text:
Research Associate in Artificial Intelligence and Software Engineering As the successful candidate, you will primarily contribute to a partnership project with BGL; BNP Paribas, one of the major banks in Luxembourg. The title of the project is “AI for AI” and it concerns the design of an AI ‘metamodel’ tool that will monitor and improve AI algorithms effectiveness and robustness, allowing their application to business-critical use cases at scale. The objective of this project is to develop automated means to continuously monitor the performance of AI models (including NLP models) developed by BGL BNP Paribas and to determine when and how to retrain these models in order to improve their performance. Achieving these objectives requires addressing crucial research challenges such as the definition of proper quality metrics across the bank’s use cases, the identification and explaination of the limitations and blanks spots of the models, and the design of sustainable improvement mechanisms The candidate should possess an PhD degree (or equivalent) in computer science with strong skills in software engineering, programming, and artificial intelligence, as well as good knowledge of computer science in general. The ideal candidate should have some knowledge and/or experience in most of the following topics: Programming (Python is a must, Java is an asset); Data science, data engineering, data collection and storage; Artificial intelligence, machine learning; Natural Language Processing is a plus (but not mandatory)
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